Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical ...
MIT researchers developed an AI tool, MultiverSeg, to simplify the annotation of medical images for clinical research.
A research team led by Prof. Wang Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
Abstract: In recent years, supervised learning using convolutional neural networks (CNN) has served as a benchmark for various medical image segmentation and classification. However, supervised ...
Spinal health forms the cornerstone of the overall human body functionality with the lumbar spine playing a critical role and prone to various types of injuries due to inflammation and diseases, ...
Abstract: Automated ultrasound (US) image analysis is hindered by challenges stemming from low resolution, noise, and non-uniform grayscale distribution, which compromise image quality. While many ...
Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
Microsoft Deployment Toolkit is designed to streamline the deployment of Windows operating systems, applications, and configurations across multiple devices. If you want to capture Windows Image using ...
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 ...
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