A review of deep-learning-based medical image segmentation methods

X Liu, L Song, S Liu, Y Zhang - Sustainability, 2021‏ - mdpi.com
As an emerging biomedical image processing technology, medical image segmentation has
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

Y Fu, Y Lei, T Wang, WJ Curran, T Liu, X Yang - Physica Medica, 2021‏ - Elsevier
Deep learning has revolutionized image processing and achieved the-state-of-art
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

Y Li, Y Zhang, W Cui, B Lei, X Kuang… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Retinal vessel segmentation with deep learning technology is a crucial auxiliary method for
clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably …

From handcrafted to deep-learning-based cancer radiomics: challenges and opportunities

P Afshar, A Mohammadi, KN Plataniotis… - IEEE Signal …, 2019‏ - ieeexplore.ieee.org
Recent advancements in signal processing (SP) and machine learning, coupled with
electronic medical record kee** in hospitals and the availability of extensive sets of …

Semantic image segmentation: Two decades of research

G Csurka, R Volpi, B Chidlovskii - Foundations and Trends® …, 2022‏ - nowpublishers.com
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 …

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia

G Chassagnon, M Vakalopoulou, E Battistella… - Medical image …, 2021‏ - Elsevier
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 …

Deeply-supervised networks with threshold loss for cancer detection in automated breast ultrasound

Y Wang, N Wang, M Xu, J Yu, C Qin… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
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 …

Computer-aided diagnosis of pulmonary fibrosis using deep learning and CT images

A Christe, AA Peters, D Drakopoulos… - Investigative …, 2019‏ - journals.lww.com
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 …

A visually interpretable deep learning framework for histopathological image-based skin cancer diagnosis

S Jiang, H Li, Z ** - IEEE Journal of Biomedical and Health …, 2021‏ - ieeexplore.ieee.org
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 …

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 …