Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
Mass General Brigham researchers are betting that the next big leap in brain medicine will come from teaching artificial ...
First 4D Radar Automatic Labelling tools using Segment Anything (SA) drivable area segmentation on camera using Deep Learning for Autonomous Vehicle. KAIST-Radar (K-Radar) (provided by 'AVELab') is a ...
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 ...
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 ...
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 ...
ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...
In this tutorial, we will show you how to upscale an image using Copilot PC. Whether you want to take a large print of a picture, improve old photos, or crop a photo to focus on the content, you can ...
1 School of Biomedical Engineering, Sichuan University, Chengdu, China 2 National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China ...
Objective: Our research aims to develop an automated method for segmenting brain CT images in healthy 2-year-old children using the ResU-Net deep learning model. Building on this model, we aim to ...
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