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A review of deep-learning-based medical image segmentation methods
As an emerging biomedical image processing technology, medical image segmentation has
made great contributions to sustainable medical care. Now it has become an important …
made great contributions to sustainable medical care. Now it has become an important …
A review of deep learning based methods for medical image multi-organ segmentation
Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …
performance in many medical image segmentation tasks. Many deep learning-based …
Dual encoder-based dynamic-channel graph convolutional network with edge enhancement for retinal vessel segmentation
Retinal vessel segmentation with deep learning technology is a crucial auxiliary method for
clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably …
clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably …
From handcrafted to deep-learning-based cancer radiomics: challenges and opportunities
Recent advancements in signal processing (SP) and machine learning, coupled with
electronic medical record kee** in hospitals and the availability of extensive sets of …
electronic medical record kee** in hospitals and the availability of extensive sets of …
Semantic image segmentation: Two decades of research
Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer
vision applications, providing key information for the global understanding of an image. This …
vision applications, providing key information for the global understanding of an image. This …
AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia
Abstract Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around
the world rapidly. Computed tomography (CT) imaging has been proven to be an important …
the world rapidly. Computed tomography (CT) imaging has been proven to be an important …
Deeply-supervised networks with threshold loss for cancer detection in automated breast ultrasound
ABUS, or Automated breast ultrasound, is an innovative and promising method of screening
for breast examination. Comparing to common B-mode 2D ultrasound, ABUS attains …
for breast examination. Comparing to common B-mode 2D ultrasound, ABUS attains …
Computer-aided diagnosis of pulmonary fibrosis using deep learning and CT images
Objectives The objective of this study is to assess the performance of a computer-aided
diagnosis (CAD) system (INTACT system) for the automatic classification of high-resolution …
diagnosis (CAD) system (INTACT system) for the automatic classification of high-resolution …
A visually interpretable deep learning framework for histopathological image-based skin cancer diagnosis
Owing to the high incidence rate and the severe impact of skin cancer, the precise diagnosis
of malignant skin tumors is a significant goal, especially considering treatment is normally …
of malignant skin tumors is a significant goal, especially considering treatment is normally …
Lung computed tomography image segmentation based on U-Net network fused with dilated convolution
K Chen, Y Xuan, A Lin, S Guo - Computer Methods and Programs in …, 2021 - Elsevier
Purpose In order to solve the problem of accurate and effective segmentation of the patient's
lung computed tomography (CT) images, so as to improve the efficiency of treating lung …
lung computed tomography (CT) images, so as to improve the efficiency of treating lung …