BioMedical Engineering OnLine最新文献

{"title":"Keypoint localization and parameter measurement in ultrasound biomicroscopy anterior segment images based on deep learning.","authors":"Miao Qinghao, Zhou Sheng, Yang Jun, Wang Xiaochun, Zhang Min","doi":"10.1186/s12938-025-01388-3","DOIUrl":"https://doi.org/10.1186/s12938-025-01388-3","url":null,"abstract":"<p><strong>Background: </strong>Accurate measurement of anterior segment parameters is crucial for diagnosing and managing ophthalmic conditions, such as glaucoma, cataracts, and refractive errors. However, traditional clinical measurement methods are often time-consuming, labor-intensive, and susceptible to inaccuracies. With the growing potential of artificial intelligence in ophthalmic diagnostics, this study aims to develop and evaluate a deep learning model capable of automatically extracting key points and precisely measuring multiple clinically significant anterior segment parameters from ultrasound biomicroscopy (UBM) images. These parameters include central corneal thickness (CCT), anterior chamber depth (ACD), pupil diameter (PD), angle-to-angle distance (ATA), sulcus-to-sulcus distance (STS), lens thickness (LT), and crystalline lens rise (CLR).</p><p><strong>Methods: </strong>A data set of 716 UBM anterior segment images was collected from Tianjin Medical University Eye Hospital. YOLOv8 was utilized to segment four key anatomical structures: cornea-sclera, anterior chamber, pupil, and iris-ciliary body-thereby enhancing the accuracy of keypoint localization. Only images with intact posterior capsule lentis were selected to create an effective data set for parameter measurement. Ten keypoints were localized across the data set, allowing the calculation of seven essential parameters. Control experiments were conducted to evaluate the impact of segmentation on measurement accuracy, with model predictions compared against clinical gold standards.</p><p><strong>Results: </strong>The segmentation model achieved a mean IoU of 0.8836 and mPA of 0.9795. Following segmentation, the binary classification model attained an mAP of 0.9719, with a precision of 0.9260 and a recall of 0.9615. Keypoint localization exhibited a Euclidean distance error of 58.73 ± 63.04 μm, improving from the pre-segmentation error of 71.57 ± 67.36 μm. Localization mAP was 0.9826, with a precision of 0.9699, a recall of 0.9642 and an FPS of 32.64. In addition, parameter error analysis and Bland-Altman plots demonstrated improved agreement with clinical gold standards after segmentation.</p><p><strong>Conclusions: </strong>This deep learning approach for UBM image segmentation, keypoint localization, and parameter measurement is feasible, enhancing clinical diagnostic efficiency for anterior segment parameters.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"53"},"PeriodicalIF":2.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12056989/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143973810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From gaps to guidelines: a process for providing guidance to bridge evidence gaps.","authors":"Olga Yaroslavtseva, Judith Gargaro, Eleni M Patsakos, Aishwarya Nair, Robert Teasell, Mark T Bayley","doi":"10.1186/s12938-025-01385-6","DOIUrl":"https://doi.org/10.1186/s12938-025-01385-6","url":null,"abstract":"<p><strong>Background: </strong>Despite the proliferation of clinical research that can be used to inform Clinical Practice Guidelines there remain many areas where the number and quality of research studies vary widely. Using the Canadian Clinical Practice Guideline for Moderate-to-Severe Traumatic Brain Injury (MOD-SEV TBI) as an example, there is a lack of robust research evidence, derived from randomized controlled trials, meta-analyses, and systematic reviews to inform the recommendations. Randomized controlled trials in this field often have limitations, such as smaller sample sizes and gender and racial disparities in enrollment, that reduce the level of evidence they can provide. Notably, evidence is often lacking in the priority areas identified by people with lived experience (PWLE) and guideline end-users.</p><p><strong>Methods: </strong>The Canadian Clinical Practice Guideline for MOD-SEV TBI rehabilitation is a Living Guideline that implemented a robust and replicable process to mitigate these issues. This process includes: 1. Identification of Priorities by PWLE of MOD-SEV TBI and Guideline End-Users; 2. Involvement of Diverse Multidisciplinary Expert Panels, Including PWLE; 3. Compilation, Review and Evaluation of Published MOD-SEV TBI Evidence; 4. Identification of Gaps in the Published Literature; 5. Formulation of Recommendations, Rigorous Grading of Available Evidence and Formal Voting; 6. Creation of Knowledge Translation and Mobilization Tools and 7. Publication of the Updated Living Guideline.</p><p><strong>Results: </strong>Since 2014-15, the Canadian TBI Living Guideline has implemented and refined this process to produce high-quality expert consensus-based recommendations and knowledge translation and mobilization tools across 21 comprehensive domains of TBI rehabilitation. There are 351 recommendations in the current version of the Canadian TBI Living Guideline; 68% of these are primarily consensus-based recommendations. Developing a comprehensive guideline in areas where research may not be present or strong ensures that the Guideline is comprehensive and addresses the priority needs of clinicians and PWLE.</p><p><strong>Conclusions: </strong>The use of robust, transparent, and replicable evidence reviews and expert consensus building process produces clinical guidelines that are relevant and applicable even when empirical data are lacking or absent. This process of developing consensus-based recommendations can be used to develop guidelines in other content areas and populations facing similar challenges.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"52"},"PeriodicalIF":2.9,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12049030/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143969048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Industrial-grade collaborative robots for motor rehabilitation after stroke and spinal cord injury: a systematic narrative review.","authors":"Aisha Raji, Urvashy Gopaul, Jessica Babineau, Milos R Popovic, Cesar Marquez-Chin","doi":"10.1186/s12938-025-01362-z","DOIUrl":"https://doi.org/10.1186/s12938-025-01362-z","url":null,"abstract":"<p><strong>Background: </strong>There is a growing interest in exploring industrial-grade collaborative robots (cobots) for rehabilitation. This review explores their application for motor rehabilitation of the upper and lower extremities after a stroke and spinal cord injury (SCI). The article highlights the inherent safety features of cobots, emphasizing their design advantages over custom-built or traditional rehabilitation robots in terms of potential safety and time efficiency.</p><p><strong>Methods: </strong>Database searches and reference list screening were conducted to identify studies relating to the use of cobots for upper and lower extremity rehabilitation among individuals with stroke and SCI. These articles were then reviewed and summarized.</p><p><strong>Results: </strong>Thirty-three studies were included in this review. The findings suggest that the use of cobots in motor rehabilitation is still in the early stages. Some of the cobots used were equipped with sensors to detect and respond to the movement of the extremities and minimize the risk of injury. This safety aspect is crucial for patients with motor impairments. Most training protocols implemented with the cobots engaged users in repetitive task-based exercises with an overall positive user experience. Thus far, these devices have been primarily evaluated in individuals with stroke and SCI that affect the lower extremities, with no study addressing upper extremity impairments. This initial focus serves as a preliminary step toward assessing their applicability for individuals with stroke and SCI.</p><p><strong>Conclusions: </strong>Cobots may have the capacity to transform therapy and support healthcare professionals in delivering more personalized and effective rehabilitation. However, there is limited evidence on their use to support upper and lower extremity rehabilitation among individuals with stroke and SCI. Further research and development are needed to refine these technologies and broaden their applications in rehabilitation settings to enhance functional recovery and overall quality of life for individuals with stroke and SCI.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"50"},"PeriodicalIF":2.9,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12042587/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143961794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in 3D-printed scaffold technologies for bone defect repair: materials, biomechanics, and clinical prospects.","authors":"Jie Sun, Cao Chen, Bo Zhang, Chen Yao, Yafeng Zhang","doi":"10.1186/s12938-025-01381-w","DOIUrl":"https://doi.org/10.1186/s12938-025-01381-w","url":null,"abstract":"<p><p>The treatment of large bone defects remains a significant clinical challenge due to the limitations of current grafting techniques, including donor site morbidity, restricted availability, and suboptimal integration. Recent advances in 3D bioprinting technology have enabled the fabrication of structurally and functionally optimized scaffolds that closely mimic native bone tissue architecture. This review comprehensively examines the latest developments in 3D-printed scaffolds for bone regeneration, focusing on three critical aspects: (1) material selection and composite design encompassing metallic; (2) structural optimization with hierarchical porosity (macro/micro/nano-scale) and biomechanical properties tailored; (3) biological functionalization through growth factor delivery, cell seeding strategies and surface modifications. We critically analyze scaffold performance metrics from different research applications, while discussing current translational barriers, including vascular network establishment, mechanical stability under load-bearing conditions, and manufacturing scalability. The review concludes with a forward-looking perspective on innovative approaches such as 4D dynamic scaffolds, smart biomaterials with stimuli-responsive properties, and the integration of artificial intelligence for patient-specific design optimization. These technological advancements collectively offer unprecedented opportunities to address unmet clinical needs in complex bone reconstruction.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"51"},"PeriodicalIF":2.9,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12042599/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143964189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The use of a convolutional neural network to automate radiologic scoring of computed tomography of paranasal sinuses.","authors":"Daniel J Lee, Mohammad Hamghalam, Lily Wang, Hui-Ming Lin, Errol Colak, Muhammad Mamdani, Amber L Simpson, John M Lee","doi":"10.1186/s12938-025-01376-7","DOIUrl":"https://doi.org/10.1186/s12938-025-01376-7","url":null,"abstract":"<p><strong>Background: </strong>Chronic rhinosinusitis (CRS) is diagnosed with symptoms and objective endoscopy or computed tomography (CT). The Lund-Mackay score (LMS) is often used to determine the radiologic severity of CRS and make clinical decisions. This proof-of-concept study aimed to develop an automated algorithm combining a convolutional neural network (CNN) for sinus segmentation with post-processing to compute LMS directly from CT scans.</p><p><strong>Results: </strong>Radiology Information System was queried for outpatient paranasal sinus CTs at a tertiary institution. We identified 1,399 CT scans which were manually labelled with LMS of individual sinuses. Seventy-seven CT scans with 13,668 coronal images were segmented manually for individual sinuses. Our model for segmentation achieved a mean Dice score of 0.85 for all sinus regions, except for the osteomeatal complex. For individual Dice scores were 0.95, 0.71, 0.78, 0.93, 0.86 for the maxillary, anterior ethmoid, posterior ethmoid, sphenoid, and frontal sinuses, respectively. LMS was computed automatically by applying adaptive image thresholding and pixel counting to the CNN's segmented regions. A convolutional neural network (CNN) model was trained to segment each sinus region. Overall, the LMS model showed a high degree of accuracy with a score of 0.92, 0.99, 0.99, 0.97, 0.99, 0.86 for the maxillary, anterior ethmoid, posterior ethmoid, sphenoid, and frontal sinuses, respectively.</p><p><strong>Conclusions: </strong>Reporting of paranasal sinus CT can be automated and potentially standardized with a CNN model to provide accurate Lund-Mackay score.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"49"},"PeriodicalIF":2.9,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12036281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143953473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of Alzheimer and mild cognitive impairment patients by Poincare and Entropy methods based on electroencephalography signals.","authors":"Umut Aslan, Mehmet Feyzi Akşahin","doi":"10.1186/s12938-025-01369-6","DOIUrl":"https://doi.org/10.1186/s12938-025-01369-6","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is characterized by deficits in cognition, behavior, and intellectual functioning, and Mild Cognitive Impairment (MCI) refers to individuals whose cognitive impairment deviates from what is expected for their age but does not significantly interfere with daily activities. Because there is no treatment for AD, early prediction of AD can be helpful to reducing the progression of this disease. This study examines the Electroencephalography (EEG) signal of 3 distinct groups, including AD, MCI, and healthy individuals. Recognizing the non-stationary nature of EEG signals, two nonlinear approaches, Poincare and Entropy, are employed for meaningful feature extraction. Data should be segmented into epochs to extract features from EEG signals, and feature extraction approaches should be implemented for each one. The obtained features are given to machine learning algorithms to classify the subjects. Extensive experiments were conducted to analyze the features comprehensively. The results demonstrate that our proposed method surpasses previous studies in terms of accuracy, sensitivity, and specificity, indicating its effectiveness in classifying individuals with AD, MCI, and those without cognitive impairment.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"47"},"PeriodicalIF":2.9,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12023449/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143965197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Complexity of post-concussion syndrome assessment and management: a case for customizing rehabilitation.","authors":"Nicholas Moser, Milos R Popovic, Sukhvinder Kalsi-Ryan","doi":"10.1186/s12938-025-01380-x","DOIUrl":"https://doi.org/10.1186/s12938-025-01380-x","url":null,"abstract":"<p><strong>Background: </strong>Post-concussion syndrome is a challenging condition to manage for even the most experienced chronic pain experts. Patients' presentations are heterogeneous with symptoms spanning physical, cognitive and emotional domains. The symptoms reported are often non-specific, making it difficult for health professionals to prescribe effective rehabilitation. The aim of the present study was to examine the effectiveness of a customized rehabilitation program based on subgroup determination following a standardized clinical exam in adults with post-concussion syndrome.</p><p><strong>Methods: </strong>A total of 16 adults (mean age ± SD, 38.3 ± 12.5 years) with post-concussion syndrome participated in a 6-week rehabilitation program. Participants were recruited from external community concussion clinics around the greater Toronto area, Canada. Participants underwent a comprehensive standardized clinical exam to subgroup the ostensible symptom generators into either autonomic, cervical or vestibulo-ocular. Customized rehabilitation was then prescribed based on their subgroupings. The primary outcome measure was the Rivermead Post-Concussion Questionnaire (RPQ). Secondary outcome measures included the Patient Health Questionnaire-9 (PHQ-9), the Neck Disability Index (NDI), and exercise tolerance as assessed via the Buffalo Concussion Treadmill Test (BCTT).</p><p><strong>Results: </strong>Following 6 weeks of customized rehabilitation, participants on average experienced a significant and clinically meaningful change with respect to the RPQ-3 and RPQ-13 (p < 0.001). We also observed a significant change in all secondary outcome measures including a reduction in PHQ-9 (p < 0.01), NDI (p < 0.001) and exercise tolerance, expressed as heart rate threshold (p < 0.001).</p><p><strong>Conclusion: </strong>The standardized exam was feasible and useful in assisting the clinician in prescribing effective rehabilitation. The 6-week customized rehabilitation program demonstrated significant changes in patient-reported persistent post-concussion symptoms and exercise tolerance. The implementation of a customized program based on a standardized exam performed to subgroup the ostensible symptom generators may be key to successful management in this population.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"48"},"PeriodicalIF":2.9,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12032806/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143958570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application and optimization of bioengineering strategies in facilitating tendon-bone healing.","authors":"Chenhui Yang, Changshun Chen, Rongjin Chen, Fei Yang, Hefang Xiao, Bin Geng, Yayi Xia","doi":"10.1186/s12938-025-01368-7","DOIUrl":"https://doi.org/10.1186/s12938-025-01368-7","url":null,"abstract":"<p><p>Tendon-bone insertion trauma is prevalent in both rotator cuff and anterior cruciate ligament injuries, which are frequently encountered conditions in the field of sports medicine. The main treatment for such injuries is reconstructive surgery. The primary determinant impacting this process is the graft's capacity to integrate with the bone tunnel. In recent years, researchers have attempted to use a variety of methods to facilitate tendon-bone healing after reconstructive surgery. Such as the implantation of biological materials, cytokines and the local application of permanently differentiated cells from various sources. However, there are limitations to the efficacy of one therapy alone in facilitating tendon-bone healing. Therefore, researchers are trying to combine strategies to overcome this conundrum. At present, most studies are based on biomaterial combined with other therapeutic strategies for tissue repair and regeneration. Biomaterials mainly include the application of bioengineering scaffolds, hydrogels and bioabsorbable interference screws. By conducting a thorough review of relevant literature, this study provides a comprehensive overview of the present research progress in enhancing tendon-bone healing using biomaterials. Additionally, it explores the potential benefits of combining biomaterials with other approaches to promote tendon-bone healing. The ultimate goal is to offer insights for future basic research endeavors and establish a solid groundwork for advancing clinical applications in the near future.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"46"},"PeriodicalIF":2.9,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12016306/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143969708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Music interventions and obstructive sleep apnea: a brain connectivity analysis.","authors":"J Rajeswari, S Navaneethan, P Siva Satya Sreedhar, M Jagannath","doi":"10.1186/s12938-025-01382-9","DOIUrl":"https://doi.org/10.1186/s12938-025-01382-9","url":null,"abstract":"<p><strong>Background: </strong>The blockage in the upper airway that occurs, while sleeping is represented as obstructive sleep apnea (OSA). This seem to be a major issue which cause breathing difficulties also increases the risk of severe complications, such as heart attacks and strokes. Therefore, in this proposed study the impact of OSA using brain connectivity analysis under various conditions such as Neelambari, Kapi, and no music has been investigated. The electroencephalogram (EEG) recordings of twelve subjects were acquired in two different conditions, such as listening to music 1 and 2 (Neelambari and Kapi) and the absence of music. The raw EEG signals were then pre-processed using both bandpass and notch filters. Meanwhile, the EEG sub-bands were obtained using the wavelet packet decomposition (WPD) method. These sub-bands, including delta, theta, alpha, and beta, were used for brain connectivity analysis. This approach provides the visualization of frequency-specific regional brain connectivity patterns by applying Pearson Correlation to the absolute values of the detail coefficients from WPD using a graph theory metric, node strength.</p><p><strong>Results: </strong>Increased connectivity in the right hemisphere of the brain was observed among the nodes in the frontal and temporal regions (F8, FC6, and T8) when participants listened to Neelambari music (Music 1). In the beta band, the correlation values for Neelambari music ranged from a minimum of 0.943 to a maximum of 0.998. In the delta band, positive correlation values ranged from 0.945 (minimum) to 0.999 (maximum). The alpha and theta bands exhibited moderate correlations, ranging from 0.746 (minimum) to 0.996 (maximum). Compared to Kapi music, Neelambari music showed stronger neural synchronization, evidenced by consistently higher correlation values across all frequency bands. This increased connectivity suggests that Neelambari music may profoundly impact brain dynamics, potentially enhancing cognitive or physiological responses.</p><p><strong>Conclusions: </strong>In conclusion, it has been analyzed that OSA patients have positive brain connectivity while listening to music 1 (Neelambari).</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"45"},"PeriodicalIF":2.9,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12016325/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143961538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Video microscopy: an old story with a bright biological future.","authors":"Léa-Isabelle Renaud, Kelliane Béland, Eric Asselin","doi":"10.1186/s12938-025-01375-8","DOIUrl":"https://doi.org/10.1186/s12938-025-01375-8","url":null,"abstract":"<p><p>Single-cell analysis is increasingly popular in the field of biology, enabling more precise analyses of heterogeneous phenomena, particularly in the fields of embryology and the study of different diseases. At the heart of this evolution is video microscopy, an ancient but revolutionary technique. From its first use on embryos, through the study of C. Elegans, with the development of algorithms for its automation, the history of video microscopy has been fascinating. Unfortunately, many unresolved issues remain, such as the sheer volume of data produced and the quality of the images taken. The aim of this review is to explore the past, present and future of this technique, which could become indispensable in recent decades, to understand cell fate and how diseases affect their destiny.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"44"},"PeriodicalIF":2.9,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004724/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144062027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}