AIMC Topic: Image Processing, Computer-Assisted
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Open-source deep-learning models for segmentation of normal structures for prostatic and gynecological high-dose-rate brachytherapy: Comparison of architectures.
Journal of applied clinical medical physics
Apr 5, 2025
BACKGROUND: The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containi...
Scale selection and machine learning based cell segmentation and tracking in time lapse microscopy.
Scientific reports
Apr 5, 2025
Monitoring and tracking of cell motion is a key component for understanding disease mechanisms and evaluating the effects of treatments. Time-lapse optical microscopy has been commonly employed for studying cell cycle phases. However, usual manual ce...
MedScale-Former: Self-guided multiscale transformer for medical image segmentation.
Medical image analysis
Apr 4, 2025
Accurate medical image segmentation is crucial for enabling automated clinical decision procedures. However, existing supervised deep learning methods for medical image segmentation face significant challenges due to their reliance on extensive label...
Retinal OCT image segmentation with deep learning: A review of advances, datasets, and evaluation metrics.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 4, 2025
Optical coherence tomography (OCT) is a widely used imaging technology in ophthalmic clinical practice, providing non-invasive access to high-resolution retinal images. Segmentation of anatomical structures and pathological lesions in retinal OCT ima...
Deep-learning synthetized 4DCT from 4DMRI of the abdominal site in carbon-ion radiotherapy.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 4, 2025
PURPOSE: To investigate the feasibility of deep-learning-based synthetic 4DCT (4D-sCT) generation from 4DMRI data of abdominal patients undergoing Carbon Ion Radiotherapy (CIRT).
AI as a decision support tool in forensic image analysis: A pilot study on integrating large language models into crime scene investigation workflows.
Journal of forensic sciences
Apr 4, 2025
This study evaluates the effectiveness of artificial intelligence (AI) tools (ChatGPT-4, Claude, and Gemini) in forensic image analysis of crime scenes, marking a significant step toward developing bespoke AI models for forensic applications. The res...
Wild horseshoe crab image denoising based on CNN-transformer architecture.
Scientific reports
Apr 4, 2025
The natural habitats of wild horseshoe crabs (such as beaches, shallow water areas, and intertidal sediments) are complex, posing challenges for image capture, which is often affected by real noise factors. Deep learning models are widely used in ima...
Robust semi-automatic vessel tracing in the human retinal image by an instance segmentation neural network.
Science advances
Apr 4, 2025
Vasculature morphology and hierarchy are essential for blood perfusion. Human retinal circulation is an intricate vascular system emerging and remerging at the optic nerve head (ONH). Tracing retinal vascular branching from ONH can allow detailed mor...
Unsupervised Domain Adaptation for Cross-Modality Cerebrovascular Segmentation.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Cerebrovascular segmentation from time-of-flight magnetic resonance angiography (TOF-MRA) and computed tomography angiography (CTA) is essential in providing supportive information for diagnosing and treatment planning of multiple intracranial vascul...
ProCNS: Progressive Prototype Calibration and Noise Suppression for Weakly-Supervised Medical Image Segmentation.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Weakly-supervised segmentation (WSS) has emerged as a solution to mitigate the conflict between annotation cost and model performance by adopting sparse annotation formats (e.g., point, scribble, block, etc.). Typical approaches attempt to exploit an...
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