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 ...
GitHub

Replace TensorFlow with PyTorch in the Segmentation machine learning code

The current Segmentation machine learning code uses TensorFlow 1 which is incompatible with Python 3.11 needed by other software packages. The thing to do is to replace TensorFlow with PyTorch since ...
Frontiers

Evaluation of retinal structure changes with AI-based OCT image segmentation for sodium iodate induced retinal degeneration

Segmentations of retinal optical coherence tomography (OCT) images provide valuable information about each specific retinal layer. However, processing images from degenerative retina remains ...
GitHub

retina-segmentation

Advanced deep learning framework for OCT retinal analysis with multi-architecture comparison for automated retinal layer segmentation, ERM detection, and vesicle analysis using state-of-the-art neural ...
IEEE

Bundleseg: two-stage retinal blood vessel segmentation based on Bundle Modulese

Abstract: This study presents an advanced two-stage retinal blood vessel segmentation network based on Bundle Modules (Bundle Segmentation Network, referred to as BD-Net), aiming to enhance the ...
IEEE

Retinal Vessel Segmentation Algorithm Based on Improved Gaussian Matched Filter

Abstract: Retinal images can assist doctors in diagnosis, and their segmentation algorithms have received widespread attention. This article proposes a retinal segmentation algorithm based on an ...