AIMC Topic: Image Interpretation, Computer-Assisted
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MEFA-Net: A mask enhanced feature aggregation network for polyp segmentation.
Computers in biology and medicine
Dec 31, 2024
Accurate polyp segmentation is crucial for early diagnosis and treatment of colorectal cancer. This is a challenging task for three main reasons: (i) the problem of model overfitting and weak generalization due to the multi-center distribution of dat...
A novel artificial intelligence segmentation model for early diagnosis of bladder tumors.
Abdominal radiology (New York)
Dec 30, 2024
OBJECTIVE: Despite cystoscopy plays an important role in bladder tumors diagnosis, it often falls short in flat cancerous tissue and minuscule satellite lesions. It can easily lead to a missed diagnosis by the urologist, which can lead to a swift tum...
AI-Driven insights in pancreatic cancer imaging: from pre-diagnostic detection to prognostication.
Abdominal radiology (New York)
Dec 30, 2024
Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the United States, largely due to its poor five-year survival rate and frequent late-stage diagnosis. A significant barrier to early detection even in high...
Cooperative multi-task learning and interpretable image biomarkers for glioma grading and molecular subtyping.
Medical image analysis
Dec 30, 2024
Deep learning methods have been widely used for various glioma predictions. However, they are usually task-specific, segmentation-dependent and lack of interpretable biomarkers. How to accurately predict the glioma histological grade and molecular su...
Intelligent cholinergic white matter pathways algorithm based on U-net reflects cognitive impairment in patients with silent cerebrovascular disease.
Stroke and vascular neurology
Dec 30, 2024
BACKGROUND AND OBJECTIVE: The injury of the cholinergic white matter pathway underlies cognition decline in patients with silent cerebrovascular disease (SCD) with white matter hyperintensities (WMH) of vascular origin. However, the evaluation of the...
Male
Middle Aged
Deep Learning
Reproducibility of Results
Aged
Aged, 80 and over
Predictive Value of Tests
Cerebrovascular Disorders
Image Interpretation, Computer-Assisted
Cognitive Dysfunction
Cognition
Magnetic Resonance Imaging
Humans
Algorithms
Female
Leukoencephalopathies
White Matter
Cholinergic Fibers
Cholinergic Neurons
Leveraging domain knowledge for synthetic ultrasound image generation: a novel approach to rare disease AI detection.
International journal of computer assisted radiology and surgery
Dec 29, 2024
PURPOSE: This study explores the use of deep generative models to create synthetic ultrasound images for the detection of hemarthrosis in hemophilia patients. Addressing the challenge of sparse datasets in rare disease diagnostics, the study aims to ...
Attention incorporated network for sharing low-rank, image and k-space information during MR image reconstruction to achieve single breath-hold cardiac Cine imaging.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dec 28, 2024
Cardiac Cine Magnetic Resonance Imaging (MRI) provides an accurate assessment of heart morphology and function in clinical practice. However, MRI requires long acquisition times, with recent deep learning-based methods showing great promise to accele...
Role of Artificial Intelligence for Endoscopic Ultrasound.
Gastrointestinal endoscopy clinics of North America
Dec 27, 2024
Endoscopic ultrasound (EUS) is widely used for the diagnosis of biliopancreatic and gastrointestinal tract diseases, but it is one of the most operator-dependent endoscopic techniques, requiring a long and complex learning curve. The role of artifici...
Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods.
Tomography (Ann Arbor, Mich.)
Dec 26, 2024
UNLABELLED: Due to the increasing number of people working at computers in professional settings, the incidence of lumbar disc herniation is increasing.
BCD-TransNet: Automatic breast cancer detection and classification using transfer learning approach.
Technology and health care : official journal of the European Society for Engineering and Medicine
Dec 25, 2024
Breast Cancer (BC) is a predominant form of cancer diagnosed in women and one of the deadliest diseases. The important cause of death owing to the cancer amongst women is BC. However, the existing ML techniques are very challenge evaluate the perform...
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