Published as an arXiv preprint, the paper details how unsupervised and self-supervised AI models are matching or surpassing ...
We provide a Dockerfile for creating a container with the required libraries installed. To build the docker image, run the following command: docker build -t growsp ...
Imaging technologies are ubiquitous in our daily lives, from smartphone cameras to medical imaging devices, helping us capture images and perceive objects. However, when faced with complex ...
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 ...
A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...
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 ...
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