Results 21 to 30 of about 29,416,981 (354)

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation [PDF]

International Conference on 3D Vision, 2016
Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most approaches are only able to process 2D images while most medical data used ...
F. Milletarì, N. Navab, Seyed-Ahmad Ahmadi   +2 more
semanticscholar   +1 more source

Foldover Features for Dynamic Object Behaviour Description in Microscopic Videos

IEEE Access, 2020
A behavior description helps analyze tiny objects, similar objects, objects with weak visual information, and objects with similar visual information. It plays a fundamental role in the identification and classification of dynamic objects in microscopic ...
Xialin Li, Chen Li, Frank Kulwa, Md Mamunur Rahaman, Wenwei Zhao, Xue Wang, Dan Xue, Yudong Yao, Yilin Cheng, Jindong Li, Shouliang Qi, Tao Jiang   +11 more
doaj   +1 more source

Application of transfer learning and ensemble learning in image-level classification for breast histopathology

Intelligent Medicine, 2023
Background: Breast cancer has the highest prevalence among all cancers in women globally. The classification of histopathological images in the diagnosis of breast cancers is an area of clinical concern.
Yuchao Zheng, Chen Li, Xiaomin Zhou, Haoyuan Chen, Hao Xu, Yixin Li, Haiqing Zhang, Xiaoyan Li, Hongzan Sun, Xinyu Huang, Marcin Grzegorzek   +10 more
doaj   +1 more source

Bidirectional Copy-Paste for Semi-Supervised Medical Image Segmentation [PDF]

Computer Vision and Pattern Recognition, 2023
In semi-supervised medical image segmentation, there exist empirical mismatch problems between labeled and un-labeled data distribution. The knowledge learned from the labeled data may be largely discarded if treating labeled and unlabeled data ...
Yun-Hao Bai, Duo-Wen Chen, Qing-Li Li, Wei-Lei Shen, Yan Wang   +4 more
semanticscholar   +1 more source

An Enhanced Framework of Generative Adversarial Networks (EF-GANs) for Environmental Microorganism Image Augmentation With Limited Rotation-Invariant Training Data

IEEE Access, 2020
The main obstacle to image augmentation with Generative Adversarial Networks (GANs) is the need for a large amount of training data, but this is difficult for small datasets like Environmental Microorganisms (EMs). EM image analysis plays a vital role in
Hao Xu, Chen Li, Md Mamunur Rahaman, Yudong Yao, Zihan Li, Jinghua Zhang, Frank Kulwa, Xin Zhao, Shouliang Qi, Yueyang Teng   +9 more
doaj   +1 more source

Customized Segment Anything Model for Medical Image Segmentation [PDF]

arXiv.org, 2023
We propose SAMed, a general solution for medical image segmentation. Different from the previous methods, SAMed is built upon the large-scale image segmentation model, Segment Anything Model (SAM), to explore the new research paradigm of customizing ...
Kaiwen Zhang, Dong Liu
semanticscholar   +1 more source

Medical image enhancement using threshold decomposition driven adaptive morphological filter [PDF]

, 2008
One of the most common degradations in medical images is their poor contrast quality. This suggests the use of contrast enhancement methods as an attempt to modify the intensity distribution of the image.
Mahmoud, Tarek A., Marshall, Stephen
core   +4 more sources

Comparative Study for Patch-Level and Pixel-Level Segmentation of Deep Learning Methods on Transparent Images of Environmental Microorganisms: From Convolutional Neural Networks to Visual Transformers

Applied Sciences, 2022
Currently, the field of transparent image analysis has gradually become a hot topic. However, traditional analysis methods are accompanied by large amounts of carbon emissions, and consumes significant manpower and material resources.
Hechen Yang, Xin Zhao, Tao Jiang, Jinghua Zhang, Peng Zhao, Ao Chen, Marcin Grzegorzek, Shouliang Qi, Yueyang Teng, Chen Li   +9 more
doaj   +1 more source

Medical emergencies in medical imaging [PDF]

BMJ Quality & Safety, 2012
Sending inpatients to the medical imaging department is sometimes tantamount to discharging them from hospital for hours at a time. Consider, for example, a patient with an unexplained acute abdomen where an urgent CT scan is indicated. Patient transport, logistical delays and the procedure itself may lead to gaps in monitoring vital signs, providing ...
John A, Staples, Donald A, Redelmeier
openaire   +2 more sources

A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): From Convolutional Neural Networks to Visual Transformers

Frontiers in Microbiology, 2022
In recent years, deep learning has made brilliant achievements in Environmental Microorganism (EM) image classification. However, image classification of small EM datasets has still not obtained good research results. Therefore, researchers need to spend
Peng Zhao, Chen Li, Md Mamunur Rahaman, Hao Xu, Hechen Yang, Hongzan Sun, Tao Jiang, Marcin Grzegorzek   +7 more
doaj   +1 more source