Recent trends in computer assisted diagnosis (CAD) system for breast cancer diagnosis using histopathological images
Breast cancer is one of the common type of cancer in females across the world. An early
detection and diagnosis of breast cancer may reduce the mortality rate to a great extent. To …
detection and diagnosis of breast cancer may reduce the mortality rate to a great extent. To …
Machine learning methods for histopathological image analysis: A review
Histopathological images (HIs) are the gold standard for evaluating some types of tumors for
cancer diagnosis. The analysis of such images is time and resource-consuming and very …
cancer diagnosis. The analysis of such images is time and resource-consuming and very …
[HTML][HTML] Computer-assisted screening for cervical cancer using digital image processing of pap smear images
KP Win, Y Kitjaidure, K Hamamoto, T Myo Aung - Applied Sciences, 2020 - mdpi.com
Cervical cancer can be prevented by having regular screenings to find any precancers and
treat them. The Pap test looks for any abnormal or precancerous changes in the cells on the …
treat them. The Pap test looks for any abnormal or precancerous changes in the cells on the …
Toward a development of general type-2 fuzzy classifiers applied in diagnosis problems through embedded type-1 fuzzy classifiers
Nowadays, with the emergence of computer-aided systems, diagnosis problems are one of
the most important application areas of artificial intelligence. The present paper is focused …
the most important application areas of artificial intelligence. The present paper is focused …
[HTML][HTML] Publicly available datasets of breast histopathology H&E whole-slide images: A sco** review
Advancements in digital pathology and computing resources have made a significant impact
in the field of computational pathology for breast cancer diagnosis and treatment. However …
in the field of computational pathology for breast cancer diagnosis and treatment. However …
Breast cancer image multi-classification using random patch aggregation and depth-wise convolution based deep-net model
Adapting the profound, deep convolutional neural network models for large image
classification can result in the layout of network architectures with a large number of …
classification can result in the layout of network architectures with a large number of …
Histopathologic image processing: A review
Histopathologic Images (HI) are the gold standard for evaluation of some tumors. However,
the analysis of such images is challenging even for experienced pathologists, resulting in …
the analysis of such images is challenging even for experienced pathologists, resulting in …
Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports
Objective: In machine learning, it is evident that the classification of the task performance
increases if bootstrap aggregation (bagging) is applied. However, the bagging of deep …
increases if bootstrap aggregation (bagging) is applied. However, the bagging of deep …
Intelligent framework for brain tumor grading using advanced feature analysis
G Mohan - Computer Methods in Biomechanics and Biomedical …, 2023 - Taylor & Francis
The analysis of digital pathology images, catalyzes research and automate diagnosis for
improving clinical care. Regardless of the advances in high-resolution and speedy scanning …
improving clinical care. Regardless of the advances in high-resolution and speedy scanning …
Masked autoencoders with handcrafted feature predictions: Transformer for weakly supervised esophageal cancer classification
Y Bai, W Li, J An, L **a, H Chen, G Zhao… - Computer Methods and …, 2024 - Elsevier
Abstract Background and Objective Esophageal cancer is a serious disease with a high
prevalence in Eastern Asia. Histopathology tissue analysis stands as the gold standard in …
prevalence in Eastern Asia. Histopathology tissue analysis stands as the gold standard in …