Accuracy analysis of deep learning methods in breast cancer classification: A structured review
Breast cancer is diagnosed using histopathological imaging. This task is extremely time-
consuming due to high image complexity and volume. However, it is important to facilitate …
consuming due to high image complexity and volume. However, it is important to facilitate …
A comprehensive review of tubule formation in histopathology images: advancement in tubule and tumor detection techniques
Breast cancer, the earliest documented cancer in history, stands as a foremost cause of
mortality, accounting for 684,996 deaths globally in 2020 (15.5% of all female cancer cases) …
mortality, accounting for 684,996 deaths globally in 2020 (15.5% of all female cancer cases) …
MENet: A Mitscherlich function based ensemble of CNN models to classify lung cancer using CT scans
Lung cancer is one of the leading causes of cancer-related deaths worldwide. To reduce the
mortality rate, early detection and proper treatment should be ensured. Computer-aided …
mortality rate, early detection and proper treatment should be ensured. Computer-aided …
[HTML][HTML] BreastMultiNet: A multi-scale feature fusion method using deep neural network to detect breast cancer
Breast cancer is predominantly seen in women and is the leading cause of death in females
worldwide. Diagnosis of breast cancer using biopsy tissue images is expensive, time …
worldwide. Diagnosis of breast cancer using biopsy tissue images is expensive, time …
Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization
Abstract Background and Objective: Early detection of colon adenomatous polyps is critically
important because correct detection of it significantly reduces the potential of developing …
important because correct detection of it significantly reduces the potential of developing …
Automatic detection of cancer metastasis in lymph node using deep learning
Lymph node metastases are one of the most indicator of some cancer types such as breast,
colon and prostate. Breast cancer mostly spreads to lymph nodes in the armpit and it is one …
colon and prostate. Breast cancer mostly spreads to lymph nodes in the armpit and it is one …
Domain generalization in computational pathology: survey and guidelines
Deep learning models have exhibited exceptional effectiveness in Computational Pathology
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
Adaptive Threshold Learning in Frequency Domain for Classification of Breast Cancer Histopathological Images
Y Liu, X Liu, Y Qi - International Journal of Intelligent Systems, 2024 - Wiley Online Library
Breast cancer has become the most common cancer in the world, and biopsy is the most
reliable and widely used technique for detecting breast cancer. However, observation of …
reliable and widely used technique for detecting breast cancer. However, observation of …
Automatic classification of pulmonary nodules in computed tomography images using pre-trained networks and bag of features
Lung cancer has the highest incidence in the world. The standard tests for its diagnostics are
medical imaging exams, sputum cytology, and lung biopsy. Computed Tomography (CT) of …
medical imaging exams, sputum cytology, and lung biopsy. Computed Tomography (CT) of …
Spppred: Sequence-based protein-peptide binding residue prediction using genetic programming and ensemble learning
Peptide-binding proteins play significant roles in various applications such as gene
expression, metabolism, signal transmission, DNA (Deoxyribose Nucleic Acid) repair, and …
expression, metabolism, signal transmission, DNA (Deoxyribose Nucleic Acid) repair, and …