The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...
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 ...
Purpose: Brain tumor segmentation with MRI is a challenging task, traditionally relying on manual delineation of regions-of-interest across multiple imaging sequences. However, this data-intensive ...
Recent research has focused on multimodal medical image segmentation. A cascaded V-net and H-DenseUNet approach have improved Dice scores, but at the expense of high computational complexity.
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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