AIMC Topic: Image Processing, Computer-Assisted
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Large-scale benchmarking and boosting transfer learning for medical image analysis.
Medical image analysis
Feb 21, 2025
Transfer learning, particularly fine-tuning models pretrained on photographic images to medical images, has proven indispensable for medical image analysis. There are numerous models with distinct architectures pretrained on various datasets using di...
(DA-U)Net: double attention UNet for retinal vessel segmentation.
BMC ophthalmology
Feb 21, 2025
BACKGROUND: Morphological changes in the retina are crucial and serve as valuable references in the clinical diagnosis of ophthalmic and cardiovascular diseases. However, the retinal vascular structure is complex, making manual segmentation time-cons...
Generalizable deep neural networks for image quality classification of cervical images.
Scientific reports
Feb 21, 2025
Successful translation of artificial intelligence (AI) models into clinical practice, across clinical domains, is frequently hindered by the lack of image quality control. Diagnostic models are often trained on images with no denotation of image qual...
Artificial intelligence-powered coronary artery disease diagnosis from SPECT myocardial perfusion imaging: a comprehensive deep learning study.
European journal of nuclear medicine and molecular imaging
Feb 20, 2025
BACKGROUND: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a well-established modality for noninvasive diagnostic assessment of coronary artery disease (CAD). However, the time-consuming and experience-...
Automatic skull reconstruction by deep learnable symmetry enforcement.
Computer methods and programs in biomedicine
Feb 20, 2025
BACKGROUND AND OBJECTIVE: Every year, thousands of people suffer from skull damage and require personalized implants to fill the cranial cavity. Unfortunately, the waiting time for reconstruction surgery can extend to several weeks or even months, es...
Seafloor debris detection using underwater images and deep learning-driven image restoration: A case study from Koh Tao, Thailand.
Marine pollution bulletin
Feb 20, 2025
Traditional detection and monitoring of seafloor debris present considerable challenges due to the high costs associated with underwater imaging devices and the complex environmental conditions in marine ecosystems. In response to these challenges, t...
T2-weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study.
Journal of applied clinical medical physics
Feb 20, 2025
PURPOSE: To compare image quality and clinical utility of a T2-weighted (T2W) 3-dimensional (3D) fast spin echo (FSE) sequence using deep learning reconstruction (DLR) versus conventional reconstruction for rectal magnetic resonance imaging (MRI).
Leveraging Radiomics and Hybrid Quantum-Classical Convolutional Networks for Non-Invasive Detection of Microsatellite Instability in Colorectal Cancer.
Molecular imaging and biology
Feb 20, 2025
PURPOSE: The goal of this study is to create a novel framework for identifying MSI status in colorectal cancer using advanced radiomics and deep learning strategies, aiming to enhance clinical decision-making and improve patient outcomes in oncology.
Robust Myocardial Perfusion MRI Quantification With DeepFermi.
IEEE transactions on bio-medical engineering
Feb 20, 2025
Stress perfusion cardiac magnetic resonance is an important technique for examining and assessing the blood supply of the myocardium. Currently, the majority of clinical perfusion scans are evaluated based on visual assessment by experienced clinicia...
Learning-based inference of longitudinal image changes: Applications in embryo development, wound healing, and aging brain.
Proceedings of the National Academy of Sciences of the United States of America
Feb 20, 2025
Longitudinal imaging data are routinely acquired for health studies and patient monitoring. A central goal in longitudinal studies is tracking relevant change over time. Traditional methods remove nuisance variation with custom pipelines to focus on ...
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