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Segmentation technique for medical image processing: A …

    https://ieeexplore.ieee.org/document/8365301
    Segmentation is one of the popular and efficient technique in context to medical image analysis. The purpose of the segmentation is to clearly extract the …

Medical Image Segmentation With Deep Atlas Prior

    https://ieeexplore.ieee.org/document/9455423
    In this paper, we propose a novel segmentation framework which integrates the medical image anatomical prior through loss into the deep learning models. The …

Medical Image Segmentation Review: The success of U …

    https://arxiv.org/abs/2211.14830
    Automatic medical image segmentation is a crucial topic in the medical domain and successively a critical counterpart in the computer-aided diagnosis paradigm. …

Medical Image Segmentation | Papers With …

    https://paperswithcode.com/task/medical-image-segmentation
    LeeJunHyun/Image_Segmentation • • 20 Feb …

Medical Image Segmentation | Papers With …

    https://paperswithcode.com/task/medical-image-segmentation/latest
    TAAL: Test-time Augmentation for Active …

[2103.10504] UNETR: Transformers for 3D Medical …

    https://arxiv.org/abs/2103.10504
    Fully Convolutional Neural Networks (FCNNs) with contracting and expanding paths have shown prominence for the majority of medical image …

3D Medical Image Segmentation using Parallel …

    https://www.sciencedirect.com/science/article/abs/pii/S0031320323001334
    Image segmentation is the task of segmenting objects of interest in a medical image and is considered an essential medical imaging process. It is routinely …

Label-Efficient Hybrid-Supervised Learning for Medical …

    https://aaai.org/papers/02026-label-efficient-hybrid-supervised-learning-for-medical-image-segmentation/
    Due to the lack of expertise for medical image annotation, the investigation of label-efficient methodology for medical image segmentation becomes a heated topic. Recent …

Deep Learning Applications in Medical Image Analysis

    https://ieeeaccess.ieee.org/featured-articles/deeplearning_image/
    The advantage of machine learning in an era of medical big data is that significant hierarchal relationships within the data can be discovered algorithmically without …

Generative adversarial networks in medical image …

    https://pubmed.ncbi.nlm.nih.gov/34864584/
    Purpose: Since Generative Adversarial Network (GAN) was introduced into the field of deep learning in 2014, it has received extensive attention from academia and industry, and a …



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