Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
GitHub

MARS-ventricles: Deep learning-based lateral ventricles segmentation

The MIAC Automated Region Segmentation (MARS) for lateral ventricles is a state-of-the-art, deep learning-based segmentation tool. This repository includes ready-to-use, pre-built container image ...
Frontiers

Deep-learning-based automatic liver segmentation using computed tomography images in dogs

Introduction: Deep learning-based automated segmentation has significantly improved the efficiency and accuracy of human medicine applications. However, veterinary applications, particularly canine ...
Frontiers

Multi-interactive feature embedding learning for medical image segmentation

1 School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China 2 School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, ...
IEEE

DEEP-MISS: Deep Learning-based Fractional Brownian Motion Integrated GAN for Medical Image Segmentation with clinical Sensors

Abstract: Medical image segmentation (MIS) plays a vital role in different medical applications like analysis, treatment planning, and diagnosis. However, the segmentation accuracy was lower due to ...
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 ...
IEEE

A Deep Learning Multimodal Fusion-Based Method for Cell and Nucleus Segmentation

Abstract: In recent years, deep learning has been widely utilized in the fields of biomedical image segmentation and cellular image analysis. Supervised deep neural networks trained on annotated data ...
marktechpost

GenSeg: Generative AI Transforms Medical Image Segmentation in Ultra Low-Data Regimes

Medical image segmentation is at the heart of modern healthcare AI, enabling crucial tasks such as disease detection, progression monitoring, and personalized treatment planning. In disciplines like ...
GitHub

jimsyjohnson/Multi-task-Deep-Learning-for-Automatic-Cancer-Segmentation-and-Classification-in-3D-CT-Scans

This project implements a multi-task nnU-Net v2 pipeline for pancreas and lesion segmentation from 3D CT scans. The model leverages a shared encoder for feature extraction and dual decoders for ...