AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Image Interpretation, Computer-Assisted

Showing 261 to 270 of 2623 articles

Clear Filters

MEFA-Net: A mask enhanced feature aggregation network for polyp segmentation.

Computers in biology and medicine
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...

Cooperative multi-task learning and interpretable image biomarkers for glioma grading and molecular subtyping.

Medical image analysis
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...

Leveraging domain knowledge for synthetic ultrasound image generation: a novel approach to rare disease AI detection.

International journal of computer assisted radiology and surgery
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
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
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...

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
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...

A wrapper method for finding optimal subset of multimodal Magnetic Resonance Imaging sequences for ischemic stroke lesion segmentation.

Computers in biology and medicine
Multimodal data, while being information-rich, contains complementary as well as redundant information. Depending on the target problem some modalities are more informative and thus relevant for decision-making. Identifying the optimal subset of moda...

Learnable color space conversion and fusion for stain normalization in pathology images.

Medical image analysis
Variations in hue and contrast are common in H&E-stained pathology images due to differences in slide preparation across various institutions. Such stain variations, while not affecting pathologists much in diagnosing the biopsy, pose significant cha...