Background: Fundus vessel segmentation is crucial for the early diagnosis of ocular diseases. However, existing deep learning-based methods, although effective for detecting coarse vessels, still face ...
Abstract: Unsupervised domain adaptation (UDA) addresses the domain shift problem by transferring knowledge from labeled source domain data (e.g. CT) to unlabeled target domain data (e.g. MRI). While ...
The first step is to generate an image. You can use any tool to generate an image. I have used Meta AI and Google AI Studio. I generated two images using the simple prompts written below: A dog riding ...
Abstract: Unsupervised brain lesion segmentation, focusing on learning normative distributions from images of healthy subjects, are less dependent on lesion-labeled data, thus exhibiting better ...
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 ...
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 ...
1 International College, Chongqing University of Posts and Telecommunications, Chongqing, China 2 Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States To ...