Results 21 to 30 of about 16,808 (228)

Robust whole slide image analysis for cervical cancer screening using deep learning

Nature Communications, 2021
Computer-assisted diagnosis is key for scaling up cervical cancer screening. However, current recognition algorithms perform poorly on whole slide image (WSI) analysis, fail to generalize for diverse staining and imaging, and show sub-optimal clinical ...
Shenghua Cheng, Sibo Liu, Jingya Yu, Gong Rao, Yuwei Xiao, Wei Han, Wenjie Zhu, Xiaohua Lv, Ning Li, Jing Cai, Zehua Wang, Xi Feng, Fei Yang, Xiebo Geng, Jiabo Ma, Xu Li, Ziquan Wei, Xueying Zhang, Tingwei Quan, Shaoqun Zeng, Li Chen, Junbo Hu, Xiuli Liu   +22 more
doaj   +1 more source

Clinical actionability of triaging DNA mismatch repair deficient colorectal cancer from biopsy samples using deep learning

EBioMedicine, 2022
Summary: Background: We aimed to develop a deep learning (DL) model to predict DNA mismatch repair (MMR) status in colorectal cancers (CRC) based on hematoxylin and eosin-stained whole-slide images (WSIs) and assess its clinical applicability.
Wu Jiang, Wei-Jian Mei, Shuo-Yu Xu, Yi-Hong Ling, Wei-Rong Li, Jin-Bo Kuang, Hao-Sen Li, Hui Hui, Ji-Bin Li, Mu-Yan Cai, Zhi-Zhong Pan, Hui-Zhong Zhang, Li Li, Pei-Rong Ding   +13 more
doaj   +1 more source

MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images [PDF]

, 2019
The analysis of glandular morphology within colon histopathology images is an important step in determining the grade of colon cancer. Despite the importance of this task, manual segmentation is laborious, time-consuming and can suffer from subjectivity ...
Chen, Hao, Dou, Qi, Gamper, Jevgenij, Graham, Simon, Heng, Pheng-Ann, Rajpoot, Nasir, Snead, David, Tsang, Yee Wah   +7 more
core   +2 more sources

Histo-fetch – On-the-fly processing of gigapixel whole slide images simplifies and speeds neural network training

Journal of Pathology Informatics, 2022
Background: Training convolutional neural networks using pathology whole slide images (WSIs) is traditionally prefaced by the extraction of a training dataset of image patches.
Brendon Lutnick, Leema Krishna Murali, Brandon Ginley, Avi Z Rosenberg, Pinaki Sarder   +4 more
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BM-Net: CNN-Based MobileNet-V3 and Bilinear Structure for Breast Cancer Detection in Whole Slide Images

Bioengineering, 2022
Breast cancer is one of the most common types of cancer and is the leading cause of cancer-related death. Diagnosis of breast cancer is based on the evaluation of pathology slides.
Jin Huang, Liye Mei, Mengping Long, Yiqiang Liu, Wei Sun, Xiaoxiao Li, Hui Shen, Fuling Zhou, Xiaolan Ruan, Du Wang, Shu Wang, Taobo Hu, Cheng Lei   +12 more
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A deep learning model based on whole slide images to predict disease-free survival in cutaneous melanoma patients

Scientific Reports, 2022
The application of deep learning on whole-slide histological images (WSIs) can reveal insights for clinical and basic tumor science investigations. Finding quantitative imaging biomarkers from WSIs directly for the prediction of disease-free survival ...
Maria Colomba Comes, Livia Fucci, Fabio Mele, Samantha Bove, Cristian Cristofaro, Ivana De Risi, Annarita Fanizzi, Martina Milella, Sabino Strippoli, Alfredo Zito, Michele Guida, Raffaella Massafra   +11 more
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Weakly supervised detection and classification of basal cell carcinoma using graph-transformer on whole slide images

Scientific Reports, 2023
The high incidence rates of basal cell carcinoma (BCC) cause a significant burden at pathology laboratories. The standard diagnostic process is time-consuming and prone to inter-pathologist variability. Despite the application of deep learning approaches
Filmon Yacob, Jan Siarov, Kajsa Villiamsson, Juulia T. Suvilehto, Lisa Sjöblom, Magnus Kjellberg, Noora Neittaanmäki   +6 more
doaj   +1 more source

Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload. [PDF]

, 2020
Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and ...
Ayyagari, Devi, Bonham, Michael J., Chamarthi, Ramachandra Vikas, Cockerell, Clay J., Feeser, Theresa A., Ianni, Julianna D., Lee, Jason B., Motaparthi, Kiran, Olsen, Thomas G., Sankarapandian, Sivaramakrishnan, Soans, Rajath E., Stavish, Coleman C.   +11 more
core   +1 more source

Diagnostic assessment of deep learning for melanocytic lesions using whole-slide pathological images

Translational Oncology, 2021
Background: Deep learning has the potential to improve diagnostic accuracy and efficiency in medical image recognition. In the current study, we developed a deep learning algorithm and assessed its performance in discriminating melanoma from nevus using ...
Wei Ba, Rui Wang, Guang Yin, Zhigang Song, Jinyi Zou, Cheng Zhong, Jingrun Yang, Guanzhen Yu, Hongyu Yang, Litao Zhang, Chengxin Li   +10 more
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Optimizing Storage and Computational Efficiency: An Efficient Algorithm for Whole Slide Image Size Reduction

Mayo Clinic Proceedings: Digital Health, 2023
Objective: To efficiently store, transfer, and analyze whole slide imaging (WSI), we developed an image-processing algorithm to remove the unneeded background in a WSI and assemble tissue-containing parts into smaller WSIs without any change in tissue ...
Shahriar Faghani, MD, D. Chamil Codipilly, MD, Mana Moassefi, MD, Prasad G. Iyer, MD, Bradley J. Erickson, MD, PhD   +4 more
doaj   +1 more source