Jan 28, 2020 · This paper presents a review of deep learning (DL) in multi-organ segmentation. We summarized the latest DL-based methods for medical image segmentation and ...
Nov 6, 2020 · We present a deep learning solution called AIMOS that automatically segments major organs (brain, lungs, heart, liver, kidneys, spleen, bladder, stomach, ...
Jun 8, 2024 · Automatic deep learning-based multi-organ segmentation methods have far outperformed traditional methods and become a new research topic.
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Deep learning has revolutionized image processing and achieved the-state-of-art performance in many medical image segmentation tasks. Many deep learning-based ...
A Review of Deep Learning based Methods for Medical Image Multi ...
www.ncbi.nlm.nih.gov › PMC8217246
May 13, 2021 · We provide a comprehensive review of recently published deep learning-based multi-organ segmentation methods.
Sep 7, 2022 · In this report, we compared three methods of organ segmentation: 2D U-Net with 2D-slices and 3D U-Net with either 3D-whole-mouse or 3D-patches.
Oct 21, 2023 · To develop a novel deep learning framework to generate multi-organ masks from CT images for 23 different body organs.
Mar 1, 2023 · We comprehensively compile 161 studies on deep learning-based multi-organ segmentation in multiple regions such as the head and neck, chest, and abdomen.
Feb 15, 2023 · In this paper, we present an open source, deep learning-enabled tool, Mouse Embryo Multi-Organ Segmentation (MEMOS), that estimates a ...
Recently, deep learning-based methods, such as U-Net [2] and nnU-Net [3], have shown promising results in multi-organ segmentation, which rely heavily on large ...