Evaluating segment anything model (SAM) on MRI scans of brain tumors
Addressing the challenge of automatically segmenting anatomical structures from brain
images has been a long-standing problem, attributed to subject-and image-based variations …
images has been a long-standing problem, attributed to subject-and image-based variations …
Continual-Zoo: Leveraging Zoo Models for Continual Classification of Medical Images
In medical imaging leveraging continual learning (CL) is key for models to adapt to new
classes and data distributions without forgetting prior knowledge. Existing CL methods often …
classes and data distributions without forgetting prior knowledge. Existing CL methods often …
Bgman: Boundary-Prior-Guided Multi-scale Aggregation Network for skin lesion segmentation
Z Huang, Y Zhao, J Li, Y Liu - International Journal of Machine Learning …, 2024 - Springer
Skin lesion segmentation is a fundamental task in the field of medical image analysis. Deep
learning approaches have become essential tools for segmenting medical images, as their …
learning approaches have become essential tools for segmenting medical images, as their …
{S-Mamba}: Small-Size-Sensitive Mamba for Lesion Segmentation
G Wang, Y Li, W Chen, M Ding, WP Cheah… - arxiv preprint arxiv …, 2024 - arxiv.org
Small lesions play a critical role in early disease diagnosis and intervention of severe
infections. Popular models often face challenges in segmenting small lesions, as it occupies …
infections. Popular models often face challenges in segmenting small lesions, as it occupies …
DEMOCRATIZING ARTIFICIAL INTELLIGENCE BASED HEALTHCARE VIA LIGHTWEIGHT, EFFICIENT AND HIGH-PERFORMANCE NEURAL NETWORKS
SR Perera - 2024 - rave.ohiolink.edu
Medical imaging has revolutionized patient care, enabling noninvasive and detailed
visualization critical for diagnosing and treating numerous conditions. However, interpreting …
visualization critical for diagnosing and treating numerous conditions. However, interpreting …