Browsing by Author "Edelmers, Edgars"
Now showing 1 - 17 of 17
Results Per Page
Sort Options
Item Adapting Classification Neural Network Architectures for Medical Image Segmentation Using Explainable AI(2025-02-13) Nikulins, Arturs; Edelmers, Edgars; Sudars, Kaspars; Polaka, Inese; Faculty of MedicineSegmentation neural networks are widely used in medical imaging to identify anomalies that may impact patient health. Despite their effectiveness, these networks face significant challenges, including the need for extensive annotated patient data, time-consuming manual segmentation processes and restricted data access due to privacy concerns. In contrast, classification neural networks, similar to segmentation neural networks, capture essential parameters for identifying objects during training. This paper leverages this characteristic, combined with explainable artificial intelligence (XAI) techniques, to address the challenges of segmentation. By adapting classification neural networks for segmentation tasks, the proposed approach reduces dependency on manual segmentation. To demonstrate this concept, the Medical Segmentation Decathlon ‘Brain Tumours’ dataset was utilised. A ResNet classification neural network was trained, and XAI tools were applied to generate segmentation-like outputs. Our findings reveal that GuidedBackprop is among the most efficient and effective methods, producing heatmaps that closely resemble segmentation masks by accurately highlighting the entirety of the target object.Item AI-Assisted Detection and Localization of Spinal Metastatic Lesions(2024-11) Edelmers, Edgars; Nikulins, Arturs; Sprudža, Klinta Luīze; Stapulone, Patrīcija; Saimons Pūce, Niks; Skrebele , Elizabete; Elīna Siņicina, Everita; Cīrule, Viktorija; Kazuša, Ance; Boločko, Katrina; Faculty of Medicine; Department of RadiologyObjectives: The integration of machine learning and radiomics in medical imaging has significantly advanced diagnostic and prognostic capabilities in healthcare. This study focuses on developing and validating an artificial intelligence (AI) model using U-Net architectures for the accurate detection and segmentation of spinal metastases from computed tomography (CT) images, addressing both osteolytic and osteoblastic lesions. Methods: Our methodology employs multiple variations of the U-Net architecture and utilizes two distinct datasets: one consisting of 115 polytrauma patients for vertebra segmentation and another comprising 38 patients with documented spinal metastases for lesion detection. Results: The model demonstrated strong performance in vertebra segmentation, achieving Dice Similarity Coefficient (DSC) values between 0.87 and 0.96. For metastasis segmentation, the model achieved a DSC of 0.71 and an F-beta score of 0.68 for lytic lesions but struggled with sclerotic lesions, obtaining a DSC of 0.61 and an F-beta score of 0.57, reflecting challenges in detecting dense, subtle bone alterations. Despite these limitations, the model successfully identified isolated metastatic lesions beyond the spine, such as in the sternum, indicating potential for broader skeletal metastasis detection. Conclusions: The study concludes that AI-based models can augment radiologists’ capabilities by providing reliable second-opinion tools, though further refinements and diverse training data are needed for optimal performance, particularly for sclerotic lesion segmentation. The annotated CT dataset produced and shared in this research serves as a valuable resource for future advancements.Item Anthropometric Evaluation of Mandibular Characteristics in the Medieval Kurdish Population of Girê Kortikê : Sex-Based Variations and Comparative Analysis(2023-09) Kavak, Vatan; Pilmane, Māra; Kažoka, Dzintra; Edelmers, Edgars; Satici, Omer; Institute of Anatomy and AnthropologyIntroduction: This research seeks to develop population-specific standards for skeletal sex determination, focusing on the medieval Kurdish population of Girê Kortikê and the mandible, a skull component presenting the highest degree of sexual dimorphism. This is the first study of its kind for this population. The research's primary objectives were to conduct anthropometric evaluations of several mandibular characteristics within this population, assess sex-based variations, determine relationships between various mandibular sizes, and contrast these findings with other existing studies. Materials and methods: A total of 121 mandibles (55 women, 66 men) were measured using 14 distinct anthropometric techniques, applying Pearson correlation coefficients, student's t-test, and principal component analysis (PCA) for comparison. Results: The study examined and discussed disparities between some chosen mandibular measurements and data from other populations. Statistically significant sex differences (p < 0.05) and correlations were identified in 12 of the anthropological measurements. The research found that the greater the height of the symphysis (GNI), the higher the foramen mentale height (FBB). Average measurements significantly deviated from the medieval Kurdish population when compared to populations in Santa Maria Xigui, Mexico (XIG), and Mexico City (MEX). Conclusion: No correlation was found between the height of the mandibular body (HML) and the mandible length (MLT). The study suggested distinct mandibular angle (MAN) sizes between sexes, indicating unique characteristics within the Girê Kortikê population, warranting further research for a more comprehensive evaluation. In conclusion, these findings emphasize the mandible's anatomical, historical, and cultural relevance in sex determination within the Girê Kortikê population.Item Automatization of CT Annotation : Combining AI Efficiency with Expert Precision(2024-01-15) Edelmers, Edgars; Kazoka, Dzintra; Bolocko, Katrina; Sudars, Kaspars; Pilmane, Mara; Institute of Anatomy and AnthropologyThe integration of artificial intelligence (AI), particularly through machine learning (ML) and deep learning (DL) algorithms, marks a transformative progression in medical imaging diagnostics. This technical note elucidates a novel methodology for semantic segmentation of the vertebral column in CT scans, exemplified by a dataset of 250 patients from Riga East Clinical University Hospital. Our approach centers on the accurate identification and labeling of individual vertebrae, ranging from C1 to the sacrum–coccyx complex. Patient selection was meticulously conducted, ensuring demographic balance in age and sex, and excluding scans with significant vertebral abnormalities to reduce confounding variables. This strategic selection bolstered the representativeness of our sample, thereby enhancing the external validity of our findings. Our workflow streamlined the segmentation process by eliminating the need for volume stitching, aligning seamlessly with the methodology we present. By leveraging AI, we have introduced a semi-automated annotation system that enables initial data labeling even by individuals without medical expertise. This phase is complemented by thorough manual validation against established anatomical standards, significantly reducing the time traditionally required for segmentation. This dual approach not only conserves resources but also expedites project timelines. While this method significantly advances radiological data annotation, it is not devoid of challenges, such as the necessity for manual validation by anatomically skilled personnel and reliance on specialized GPU hardware. Nonetheless, our methodology represents a substantial leap forward in medical data semantic segmentation, highlighting the potential of AI-driven approaches to revolutionize clinical and research practices in radiology.Item Comparison of Bone Quality in Middle Ages and Late Modern Period Human Skeletons from Latvia(2023-07-14) Šerstņova, Ksenija; Edelmers, Edgars; Zolovs, Maksims; Pilmane, Māra; Institute of Anatomy and Anthropology; Statistics UnitThe analysis of bone microstructure and histological examination currently provides valuable insights into various facets of bone biology, ancient human existence, and bone-related diseases. This study aims to scrutinize the microstructure of historic Latvian bones, with three bone element groups selected (humerus, radius, and ulna) from a skeletal collection spanning from the Middle Ages to the Late Modern Period, procured through an archaeological excavation at St. George’s Church in Riga. To evaluate the changes in bone samples over time, two methods are utilized: (i) micro-computed tomography, used for measuring and calculating bone volume/trabecular volume (BV/TV), cortical bone and trabecular thickness, and trabecular pore diameter; (ii) immunohistochemistry (IHC) is employed to detect the presence of Runx2, OPG, OC, MMP2, TIMP2, BFGF, IL-1, IL-10, OPN, defensin-2, BMP 2/4, TGFβ factor in bone cells—specifically osteocytes. Archaeological human bone remains from the Middle Ages period in Latvia display a decline in the average bone volume to trabecular volume ratio when compared with the Late Modern Period, indicating a potential reduction in bone quality in the skeletons, potentially associated with a lower living standard during the earlier era. Comparing factors between the periods reveals a higher value of TIMP2 (p = 0.047) in samples from the Late Modern Period group, while IL-1 is higher (p = 0.036) in the Middle Ages group, which may suggest the presence of disease and diminished bone quality in the skeletons from the Middle Ages.Item Creation of Anatomically Correct and Optimized for 3D Printing Human Bones Models(2021-09-13) Edelmers, Edgars; Kažoka, Dzintra; Pilmane, Māra; Institute of Anatomy and AnthropologyEducational institutions in several countries state that the education sector should be modernized to ensure a contemporary, individualized, and more open learning process by introducing and developing advance digital solutions and learning tools. Visualization along with 3D printing have already found their implementation in different medical fields in Pauls Stradiņš Clinical University Hospital, and Rīga Stradiņš University, where models are being used for prosthetic manufacturing, surgery planning, simulation of procedures, and student education. The study aimed to develop a detailed methodology for the creation of anatomically correct and optimized models for 3D printing from radiological data using only free and widely available software. In this study, only free and cross-platform software from widely available internet sources has been used—“Meshmixer”, “3D Slicer”, and “Meshlab”. For 3D printing, the Ultimaker 5S 3D printer along with PLA material was used. In its turn, radiological data have been obtained from the “New Mexico Decedent Image Database”. In total, 28 models have been optimized and printed. The developed methodology can be used to create new models from scratch, which can be used will find implementation in different medical and scientific fields—simulation processes, anthropology, 3D printing, bioprinting, and education.Item Different Techniques of Creating Bone Digital 3D Models from Natural Specimens(2022-08) Edelmers, Edgars; Kažoka, Dzintra; Bolocko, Katrina; Pilmane, Mara; Institute of Anatomy and AnthropologyThe choice of technique for the creation of a 3D digital human bone model from natural specimens has a critical impact on the final result and usability of the obtained model. The cornerstone factor in 3D modeling is the number of faces of polygon mesh, along with topological accuracy, as well as resolution and level of detail of the texture map. Three different techniques (3D scanning, photogrammetry, and micro-computed tomography) have been used to create a digital 3D model of the human zygomatic bone. As implementation and use of 3D models can be divided into three main categories—visualization, simulation, and physical replication to obtain a functioning model (implant or prothesis)—the obtained models have been evaluated by the density and topological accuracy of the polygonal mesh, as well as by visual appearance by inspecting the obtained texture map. The obtained data indicate that for biomedical applications and computer biomechanical simulation the most appropriate technique of 3D model obtainment is micro-computed tomography, in its turn for visualization and educational purposes, the photogrammetry technique is a more preferable choice.Item Evaluation of the Impact of Nutrition Knowledge on Nutrition Behaviour and Diet in a Physically Active Person's Cohort(2023-04-01) Pļaviņa, Liāna; Umbraško, Silvija; Asare, Lāsma; Edelmers, Edgars; Institute of Anatomy and Anthropology; Statistics UnitSpecific high physical and psychological load energy expenditure should be covered by balanced diet that is adapted to physical load. Food intake is one of the vital processes that support body activity and maintain physical working capacity in special environment. Various objective and subjective factors have an impact on body energy expenditure and determine a definite amount of food energy. Dietary intake influences the readiness and training performance outcome. The purpose of the study was to evaluate the diet of physically active persons before and after a nutritional education course and determine the impact of nutrition knowledge on nutrition behaviour and diet in two subgroups: respondents with a standard BMI level (BMI < 25, in the interval 18.5-24.9) and overweight respondents with BMI ³ 25, in the interval 25.0-29.9. Participants aged 22-35 years, who had daily physical activity and physical load, were selected for the study group. We divided respondents into two subgroups: respondents with standard BMI level (BMI < 25; BMI in the interval 18.5-24.9) and overweight respondents with BMI ³ 25 (BMI in the interval 25.0-29.9). Nutritional education course included the theoretical part (lectures) and practical part (dietary diary self-assessment) as well as a quiz that allow to evaluate nutrition knowledge level in the selected cohort of respondents with BMI < 25 and BMI ³ 25. We provided intervention before and after a nutritional education course by using the standardised questionnaire "Diet 3-day menu diary"and standardised survey "Physical activity during the current life period", which allowed to evaluate the balance between the daily intake for energy recovery and daily physical activity as energy expenditure. We determined the value of the main dietary components (protein (%), carbohydrates (%) and fat (%), as well the total amount of energy (kcal) in the diet before the nutritional education course (Diet 1st) and after the nutritional education course (Diet 2nd) in the selected cohort of respondents with BMI < 25 and BMI ³ 25. The study group participants preferred a diet with a higher amount of fat and lower amount of carbohydrates compared with nutritional recommendation for general population. There were no significant differences in Diet 1st components between overweight and standard BMI groups. Analysis of post-course (Diet 2nd) dietary diary showed a statistically exact significance of fat level (%) and carbohydrate level (%), and no statistically approved changes in protein level (%) intake. Nutritional knowledge of the study group participants after the nutritional education course was evaluated by using a standardised test in points (1-10), which showed that about 60% of the respondents received an assessment "good". The results of the study can be used to develop optimal diet planning during the pre-training period before planning physical exercises with high physical and psycho-emotional load, in order to benefit physical exercise performance.Item Facilitating Student Understanding through Incorporating Digital Images and 3D-Printed Models in a Human Anatomy Course(2021-08) Kažoka, Dzintra; Pilmane, Māra; Edelmers, Edgars; Institute of Anatomy and AnthropologyCombining classical educational methods with interactive three-dimensional (3D) visualization technology has great power to support and provide students with a unique opportunity to use them in the study process, training, and/or simulation of different medical procedures in terms of a Human Anatomy course. In 2016, Rīga Stradiņš University (RSU) offered students the 3D Virtual Dissection Table “Anatomage” with possibilities of virtual dissection and digital images at the Department of Morphology. The first 3D models were printed in 2018 and a new printing course was integrated into the Human Anatomy curriculum. This study was focused on the interaction of students with digital images, 3D models, and their combinations. The incorporation and use of digital technologies offered students great tools for their creativity, increased the level of knowledge and skills, and gave them a possibility to study human body structures and to develop relationships between basic and clinical studies.Item Interdisciplinary Simulation-Based Education Curriculums on Patient Rights : For the Safety of Healthcare Professionals and Patients(2024-08-01) Slavinska, Andreta; Šāberte, Laura; Birzniece, Marika Daila; Grigoroviča, Evita; Edelmers, Edgars; Palkova, Karina; Pētersons, Aigars; Medical Education Technology Centre; Faculty of Social Sciences; Rīga Stradiņš UniversityIn 2020, the World Health Organisation (WHO) published the document “Charter: Health Worker Safety: a Priority for Patient Safety,” which emphasised the importance of enhancing health worker safety to improve patient safety. The significance of patient safety remains undiminished, as evidenced by the recent WHO document, “Patient Safety Rights Charter” (2024), which encompasses critical aspects of patient rights. It must be acknowledged that patient safety is intricately linked to the domain of patient rights, which underpins the necessity for healthcare professionals to possess interdisciplinary competence to effectively fulfil their duties and provide comprehensive patient care. However, it is essential to accurately determine and justify the specific knowledge and skills from other fields that are necessary for healthcare professionals. Moreover, healthcare specialists must not only acquire knowledge but also develop the ability to apply and integrate it into professional practice—participation in interdisciplinary clinical simulations that incorporate aspects of patient rights enables learners to think and act in clinical situations according to generally accepted algorithms and evidence-based practices, while considering the legal aspects of patients' rights. This study was carried out at the Medical Education Technology Centre, Rīga Stradiņš University, between 2023 and 2024, involving 107 residents from different specialties. The survey results reflect a strong interest and positive attitude towards interdisciplinary simulation-based training on patient rights, with participants emphasising its significance and value in enhancing resident education, highlighting the need for its continued and expanded implementation.Item Longitudinal Analysis of Latvian Child Growth : Anthropometric Parameters Dynamics from Birth to Adolescence(2024-04-03) Umbraško, Silvija; Martinsone-Berzkalne, Liene; Plavina, Liana; Cauce, Vinita; Edelmers, Edgars; Starikovs, Aleksandrs; Vetra, Janis; Institute of Anatomy and Anthropology; Statistics UnitThis study provides a comprehensive analysis of the physical development patterns from birth to adolescence, utilizing a longitudinal dataset of 70 children monitored from birth until 17 years of age. The research focuses on the variability of growth trajectories, emphasizing the role of genetic and environmental factors in influencing these patterns. Key findings indicate that most children undergo one or two periods of accelerated growth, with significant variability in the timing and magnitude of these growth spurts. The study also highlights the adaptive nature of growth changes over generations, influenced by ecological, nutritional, and socio-economic conditions. The longitudinal approach reveals critical insights into the timing of peak growth velocities, demonstrating that girls reach their growth peak approximately one year earlier than boys. The analysis of intergenerational growth patterns suggests a significant increase in average height over the century, attributed to genetic diversity and changes in lifestyle and nutrition. This study’s findings emphasize the importance of updating physical development standards regularly to reflect the changing genetic and environmental landscape. The variability in growth patterns and their correlation with health outcomes in later life highlights the need for targeted public health strategies that address the underlying socio-economic and environmental determinants of health. This research contributes to the understanding of physical development trajectories and provides a foundation for future studies aimed at optimizing health outcomes from early childhood through adolescence. The primary objective of this article is to meticulously analyze the dynamics of height growth and accurately identify the periods of accelerated bodily development within the context of longitudinal research.Item Modular Neural Networks for Osteoporosis Detection in Mandibular Cone-Beam Computed Tomography Scans(2023-10) Namatevs, Ivars; Nikulins, Arturs; Edelmers, Edgars; Neimane, Laura; Slaidiņa, Anda; Radziņš, Oskars; Sudars, Kaspars; Department of Morphology; Institute of Anatomy and Anthropology; Department of Conservative Dentistry and Oral Health; Department of Prosthetic Dentistry; Department of OrthodonticsIn this technical note, we examine the capabilities of deep convolutional neural networks (DCNNs) for diagnosing osteoporosis through cone-beam computed tomography (CBCT) scans of the mandible. The evaluation was conducted using 188 patients’ mandibular CBCT images utilizing DCNN models built on the ResNet-101 framework. We adopted a segmented three-phase method to assess osteoporosis. Stage 1 focused on mandibular bone slice identification, Stage 2 pinpointed the coordinates for mandibular bone cross-sectional views, and Stage 3 computed the mandibular bone’s thickness, highlighting osteoporotic variances. The procedure, built using ResNet-101 networks, showcased efficacy in osteoporosis detection using CBCT scans: Stage 1 achieved a remarkable 98.85% training accuracy, Stage 2 minimized L1 loss to a mere 1.02 pixels, and the last stage’s bone thickness computation algorithm reported a mean squared error of 0.8377. These findings underline the significant potential of AI in osteoporosis identification and its promise for enhanced medical care. The compartmentalized method endorses a sturdier DCNN training and heightened model transparency. Moreover, the outcomes illustrate the efficacy of a modular transfer learning method for osteoporosis detection, even when relying on limited mandibular CBCT datasets. The methodology given is accompanied by the source code available on GitLab.Item Narrative Review of Legal Aspects in the Integration of Simulation-Based Education into Medical and Healthcare Curricula(2024-03-14) Slavinska, Andreta; Palkova, Karina; Grigorovica, Evita; Edelmers, Edgars; Pētersons, Aigars; Medical Education Technology Centre; Juridiskā fakultāte; Rīga Stradiņš UniversityThe quality of healthcare varies significantly from one country to another. This variation can be attributed to several factors, including the level of healthcare professionals’ professionalism, which is closely linked to the quality of their education. Medical and healthcare education is unique in its need for students to learn and practice various clinical skills, algorithms, and behaviours for clinical situations. However, it is challenging to ensure these educational experiences do not compromise the quality of healthcare and patient safety. A simulation-based educational (SBE) approach offers a solution to these challenges. However, despite the widespread adoption of the SBE approach in medical and healthcare education curricula; its recognition for its high value among students, educators, and healthcare professionals; and evidence showing its positive impact on reducing risks to both patients and healthcare professionals, there is still an absence of a standardized approach and guidelines for integrating simulations, which includes determining when, how, and to what ex-tent they should be implemented. Currently, there is no regulation on the need for SBE integration in medical and healthcare curricula. However, the framework of this article, based on the results of the analysis of the legal framework, which includes a set of laws, regulations, principles, and standards set by various government, administrations, and authoritative institutions, will determine the fundamental aspects of the integration of the SBE approach that justify and argue the need to (1) incorporate simulation-based education across all levels of medical and healthcare education programs and (2) adhere to certain standards when integrating the SBE approach into medical and healthcare programs. This is an area that needs to be developed with the involvement of legal, health, and education experts.Item Physical Development of Six-and Seven-Year-Old Children in Riga and Latvian Regions(2023-02-01) Umbraško, Silvija; Vētra, Jānis; Pļaviņa, Liāna; Martinsone-Bērzkalne, Liene; Duļevska, Ilva; Edelmers, Edgars; Institute of Anatomy and AnthropologyThe growth and maturation of a child's body are going on continuously, but unevenly. Therefore, children of the same age may have different growth and functional abilities. On the initiative of the Latvian government, a pilot project was launched, which aims to evaluate the readiness of children to start school at the age of six as well as compare physical development, separate functional abilities, and posture for six and seven-year-old children of regions of Latvia and Riga preschool educational institutions. The study involved 918 children, who were divided into two groups-Riga (R) and regions of Latvia (RL). Respondents in each group were further divided by age-six-and seven-year-olds, and by sex. Anthropometric parameters were determined for each individual's height, weight, chest circumference, lung vital capacity (PVC), forearm flexor muscle strength, and posture. In our study, the mean values of height for six-year-old girls were: R-117.6 ± 5.8 cm, RL-117.1 ± 6.3 cm, for boys R-118.7 ± 5.0 cm, RL-118.6 ± 5.1 cm. Seven-year-old children had an average increase in chest circumference of 1 to 2 cm, both by sex and by place of residence. Symmetrical posture was observed only for six-year-old children in 23.1% of cases and 17.1% of seven-year-old children. 59.5% of the children in the study group spent more than one hour a day watching TV, and 66.3% played computer games every day. The results of the study showed that children aged six and seven years grew and functionally developed very differently and individually. These age groups of children did not have accelerated growth ages; there were no large annual increases. A relatively small sex dimorphism was observed. The readiness of six-year-old children to start school should be assessed very individually by the child's parents in collaboration with the pediatrician.Item Pilot Study on the Physical, Chemical, and Biological Determinants of Indoor Air Quality in University Classrooms(2023-11) Edelmers, Edgars; Kauce, Rūta; Konopecka, Vita; Veignere , Elizabete; Sprūdža, Klinta Luīze; Neļķe , Valters; Citskovska , Elizabete; Šipilova , Viktorija; Čikuts , Matīss; Skrebele , Elizabete; Skadiņš, Ingus; Martinsone, Žanna; Borodinecs , Anatolijs; Rīga Stradiņš UniversityIn the context of an escalating energy crisis, the burgeoning prevalence of remote work,and challenging climatic conditions, ensuring optimal indoor air quality (IAQ) has emerged as a pressing concern. This pilot study rigorously investigates the complex interplay between biological, chemical, and physical parameters that characterize IAQ, focusing specifically on university classrooms during active teaching sessions. Employing a comprehensive array of instrumentation – such as SAS SUPER ISO 100 for microbiological sampling, Aranet4 for monitoring relative humidity, temperature, and CO2 concentration, and PCE-PCO 1 and PCE-RSCM 16 for particulate matter (PM2.5 and PM10) quantification—the study spanned a duration of three days in November 2022 and covered classrooms of varying dimensions, both reliant on natural ventilation. An extensive collection of 52 microbiological samples were obtained and cultured on specialized growth media to differentiate between various classes of airborne microorganisms. Concurrently, the pilot study meticulously recorded students' activity patterns,along with the temporal dynamics of window openings and closures. The colony-forming units per cubic meter (CFU/m3) fluctuated between 174 and 934 CFU/m3, with fungi constituting the majority. Furthermore, the CFU/m3 for fungi cultivated on Sabouraud Dextrose Agar ranged from 24 to 610 CFU/m3, whereas bacteria cultured on Trypticase Soy Agar and Mannitol Salt Agar exhibited ranges of 42–476 CFU/m3 and 42–254 CFU/m3, respectively. Contrasting these findings with extant guidelines that recommend microbiological contamination not exceeding 500CFU/m3 highlights significant IAQ concerns. Thermal assessments revealed that the smaller classroom surpassed the acceptable indoor temperature threshold of 25 °C within an average duration of 50 minutes, while the larger classroom remained compliant. Notably, the highest CO2concentrations recorded over the three-day period were alarmingly high: 2689 ppm, 1970 ppm,and 2131 ppm on the first, second, and third days, respectively. A 25-minute ventilation intervention was sufficient to reduce CO2 levels to 499 ppm, although existing literature stipulatest hat CO2 concentrations should not surpass 1000 ppm. Importantly, the pilot study highlighted the rapid increasing of PM2.5 and PM10 concentrations in crowded instructional settings,averaging 400 μg/m3 and 35 μg/m3, respectively. This underscores the necessity for a continuous air ventilation and purification mechanism during classroom activities. Despite these pivotal findings, the study identifies a glaring absence of standardized regulations or guidelines pertaining to maximum acceptable concentrations of particulate matter and microbial CFU in public indoor environments, indicating a critical area requiring immediate policy intervention.Item RaspberrySet : Dataset of Annotated Raspberry Images for Object Detection(2023-05) Strautiņa, Sarmīte; Kalniņa, Ieva; Kaufmane, Edīte; Sudars, Kaspars; Namatēvs, Ivars; Nikulins, Arturs; Edelmers, EdgarsThe RaspberrySet dataset is a valuable resource for those working in the field of agriculture, particularly in the selection and breeding of ecologically adaptable berry cultivars. This is because long-term changes in temperature and weather patterns have made it increasingly important for crops to be able to adapt to their environment. To assess the suitability of different cultivars or to make yield predictions, it is necessary to describe and evaluate berries’ characteristics at various growth stages. This process is typically carried out visually, but it can be time-consuming and labor-intensive, requiring significant expert knowledge. The RaspberrySet dataset was created to assist with this process, and it includes images of raspberry berries at five different stages of development. These stages are flower buds, flowers, unripe berries, and ripe berries. All these stages of raspberry images classified buds, damaged buds, flowers, unripe berries, and ripe berries and were annotated using ground truth ROI and presented in YOLO format. The dataset includes 2039 high-resolution RGB images, with a total of 46,659 annotations provided by experts using Label Studio software (1.7.1). The images were taken in various weather conditions, at different times of the day, and from different angles, and they include fully visible buds, flowers, berries, and partially obscured buds. This dataset is intended to improve the efficiency of berry breeding and yield estimation and to identify the raspberry phenotype more accurately. It may also be useful for breeding other fruit crops, as it allows for the reliable detection and phenotyping of yield components at different stages of development. By providing a homogenized dataset of images taken on-site at the Institute of Horticulture in Dobele, Latvia, the RaspberrySet dataset offers a valuable resource for those working in horticulture. Dataset: https://doi.org/10.5281/zenodo.7014728 Dataset License: CC BY 4.0.Item Three-Dimensional Imaging in Agriculture: Challenges and Advancements in the Phenotyping of Japanese Quinces in Latvia(2023-12-17) Kaufmane, Edīte; Edelmers, Edgars; Sudars, Kaspars; Namatevs, Ivars; Nikulins, Arturs; Strautiņa, Sarmīte; Kalniņa, Ieva; Peter, Astile; Medical Education Technology CentreThis study presents an innovative approach to fruit measurement using 3D imaging, focusing on Japanese quince (Chaenomeles japonica) cultivated in Latvia. The research consisted of two phases: manual measurements of fruit parameters (length and width) using a calliper and 3D imaging using an algorithm based on k-nearest neighbors (k-NN), the ingeniously designed “Imaginary Square” method, and object projection analysis. Our results revealed discrepancies between manual measurements and 3D imaging data, highlighting challenges in the precision and accuracy of 3D imaging techniques. The study identified two primary constraints: variability in fruit positioning on the scanning platform and difficulties in distinguishing individual fruits in close proximity. These limitations underscore the need for improved algorithmic capabilities to handle diverse spatial orientations and proximities. Our findings emphasize the importance of refining 3D scanning techniques for better reliability and accuracy in agricultural applications. Enhancements in image processing, depth perception algorithms, and machine learning models are crucial for effective implementation in diverse agricultural scenarios. This research not only contributes to the scientific understanding of 3D imaging in horticulture but also underscores its potential and limitations in advancing sustainable and productive farming practices.