A survey on incorporating domain knowledge into deep learning for medical image analysis
Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
A review of explainable deep learning cancer detection models in medical imaging
Deep learning has demonstrated remarkable accuracy analyzing images for cancer
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …
High-accuracy prostate cancer pathology using deep learning
Deep learning (DL) is a powerful methodology for the recognition and classification of tissue
structures in digital pathology. Its performance in prostate cancer pathology is still under …
structures in digital pathology. Its performance in prostate cancer pathology is still under …
Deep learning in digital pathology image analysis: a survey
Deep learning (DL) has achieved state-of-the-art performance in many digital pathology
analysis tasks. Traditional methods usually require hand-crafted domain-specific features …
analysis tasks. Traditional methods usually require hand-crafted domain-specific features …
A multi-resolution model for histopathology image classification and localization with multiple instance learning
Large numbers of histopathological images have been digitized into high resolution whole
slide images, opening opportunities in developing computational image analysis tools to …
slide images, opening opportunities in developing computational image analysis tools to …
[HTML][HTML] Convolutional neural networks for computer-aided detection or diagnosis in medical image analysis: An overview
J Gao, Q Jiang, B Zhou, D Chen - Mathematical Biosciences and …, 2019 - aimspress.com
Computer-aided detection or diagnosis (CAD) has been a promising area of research over
the last two decades. Medical image analysis aims to provide a more efficient diagnostic and …
the last two decades. Medical image analysis aims to provide a more efficient diagnostic and …
Automated prostate cancer grading and diagnosis system using deep learning-based Yolo object detection algorithm
Purpose: Developing an artificial intelligence-based prostate cancer detection and
diagnosis system that can automatically determine important regions and accurately classify …
diagnosis system that can automatically determine important regions and accurately classify …
Going deeper through the Gleason scoring scale: An automatic end-to-end system for histology prostate grading and cribriform pattern detection
J Silva-Rodríguez, A Colomer, MA Sales… - Computer methods and …, 2020 - Elsevier
Abstract Background and Objective Prostate cancer is one of the most common diseases
affecting men worldwide. The Gleason scoring system is the primary diagnostic and …
affecting men worldwide. The Gleason scoring system is the primary diagnostic and …
Computer-aided cervical cancer diagnosis using time-lapsed colposcopic images
Cervical cancer causes the fourth most cancer-related deaths of women worldwide. Early
detection of cervical intraepithelial neoplasia (CIN) can significantly increase the survival …
detection of cervical intraepithelial neoplasia (CIN) can significantly increase the survival …
Axillary lymph node metastasis status prediction of early-stage breast cancer using convolutional neural networks
YW Lee, CS Huang, CC Shih, RF Chang - Computers in Biology and …, 2021 - Elsevier
Deep learning (DL) algorithms have been proven to be very effective in a wide range of
computer vision applications, such as segmentation, classification, and detection. DL …
computer vision applications, such as segmentation, classification, and detection. DL …