Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
Frontiers

Editorial: Explainable, trustworthy, and responsible AI in image processing

The tremendous growth of deep learning models, especially the success of generative AI and foundation models, has led to their deployment in several critical sectors, including biometric recognition, ...
IEEE

Comprehensive Framework for Tuberculosis Detection Using Deep Learning and Image Processing in Whole-Slide Images

Abstract: Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTb), remains one of the leading causes of death globally, primarily affecting the lungs. Recent technological advancements have ...
C&EN

Leveraging Deep Learning to Address Diagnostic Challenges with Insufficient Image Data

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...
Frontiers

Deep learning-driven medical image analysis for computational material science applications

Introduction: Deep learning has significantly advanced medical image analysis, enabling precise feature extraction and pattern recognition. However, its application in computational material science ...
IEEE

Breast Cancer Detection Using Mammography: Image Processing to Deep Learning

Abstract: Breast cancer stands as a predominant health concern for women globally. As mammography is the primary screening tool for breast cancer detection, improving the detection of breast cancer at ...