Results 11 to 20 of about 261,899 (291)

Deep Learning Based Analysis of Histopathological Images of Breast Cancer

Frontiers in Genetics, 2019
Breast cancer is associated with the highest morbidity rates for cancer diagnoses in the world and has become a major public health issue. Early diagnosis can increase the chance of successful treatment and survival. However, it is a very challenging and
Juanying Xie, Ran Liu, Joseph Luttrell, Chaoyang Zhang   +3 more
doaj   +3 more sources

Gigapixel Histopathological Image Analysis Using Attention-Based Neural Networks

IEEE Access, 2021
Although CNNs are widely considered as the state-of-the-art models in various applications of image analysis, one of the main challenges still open is the training of a CNN on high resolution images.
Nadia Brancati, Giuseppe De Pietro, Daniel Riccio, Maria Frucci   +3 more
doaj   +1 more source

Histopathological Image Analysis: A Review [PDF]

IEEE Reviews in Biomedical Engineering, 2009
Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form ...
Gurcan, Metin N., Boucheron, Laura E., Can, Ali, Madabhushi, Anant, Rajpoot, Nasir M., Yener, Bülent   +5 more
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Fusing pre-trained convolutional neural networks features for multi-differentiated subtypes of liver cancer on histopathological images

BMC Medical Informatics and Decision Making, 2022
Liver cancer is a malignant tumor with high morbidity and mortality, which has a tremendous negative impact on human survival. However, it is a challenging task to recognize tens of thousands of histopathological images of liver cancer by naked eye ...
Xiaogang Dong, Min Li, Panyun Zhou, Xin Deng, Siyu Li, Xingyue Zhao, Yi Wu, Jiwei Qin, Wenjia Guo   +8 more
doaj   +1 more source

Similar image search for histopathology: SMILY [PDF]

npj Digital Medicine, 2019
AbstractThe increasing availability of large institutional and public histopathology image datasets is enabling the searching of these datasets for diagnosis, research, and education. Although these datasets typically have associated metadata such as diagnosis or clinical notes, even carefully curated datasets rarely contain annotations of the location
Narayan Hegde, Jason D. Hipp, Yun Liu, Michael Emmert-Buck, Emily Reif, Daniel Smilkov, Michael Terry, Carrie J. Cai, Mahul B. Amin, Craig H. Mermel, Phil Q. Nelson, Lily H. Peng, Greg S. Corrado, Martin C. Stumpe   +13 more
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Progress of Machine Vision in the Detection of Cancer Cells in Histopathology

IEEE Access, 2022
In recent years, with the rapid development of artificial intelligence, machine vision technology has been widely used in various fields. Traditional cancer detection methods are time-consuming, labor-intensive, and highly dependent on the experience of ...
Wenbin He, Yongjie Han, Wuyi Ming, Jinguang Du, Yinxia Liu, Yuan Yang, Leijie Wang, Yongqiang Wang, Zhiwen Jiang, Chen Cao, Jie Yuan   +10 more
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Multi-Classification of Breast Cancer Lesions in Histopathological Images Using DEEP_Pachi: Multiple Self-Attention Head

Diagnostics, 2022
Introduction and Background: Despite fast developments in the medical field, histological diagnosis is still regarded as the benchmark in cancer diagnosis.
Chiagoziem C. Ukwuoma, Md Altab Hossain, Jehoiada K. Jackson, Grace U. Nneji, Happy N. Monday, Zhiguang Qin   +5 more
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Pan-cancer classifications of tumor histological images using deep learning [PDF]

, 2020
Histopathological images are essential for the diagnosis of cancer type and selection of optimal treatment. However, the current clinical process of manual inspection of images is time consuming and prone to intra- and inter-observer variability. Here we
Caruana, Dennis, Chuang, Jeffrey H., Farahmand, Saman, Foroughi pour, Ali, Namburi, Sandeep, Noorbakhsh, Javad, Rimm, David, Soltanieh-Ha, Mohammad, Zarringhalam, Kourosh   +8 more
core   +1 more source

3E-Net: Entropy-Based Elastic Ensemble of Deep Convolutional Neural Networks for Grading of Invasive Breast Carcinoma Histopathological Microscopic Images

Entropy, 2021
Automated grading systems using deep convolution neural networks (DCNNs) have proven their capability and potential to distinguish between different breast cancer grades using digitized histopathological images.
Zakaria Senousy, Mohammed M. Abdelsamea, Mona Mostafa Mohamed, Mohamed Medhat Gaber   +3 more
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Detection and Classification of Histopathological Breast Images Using a Fusion of CNN Frameworks

Diagnostics, 2023
Breast cancer is responsible for the deaths of thousands of women each year. The diagnosis of breast cancer (BC) frequently makes the use of several imaging techniques.
Ahsan Rafiq, Alexander Chursin, Wejdan Awad Alrefaei, Tahani Rashed Alsenani, Ghadah Aldehim, Nagwan Abdel Samee, Leila Jamel Menzli   +6 more
doaj   +1 more source