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) …
Breast Cancer Histopathological Images Segmentation Using Deep Learning
Hospitals generate a significant amount of medical data every day, which constitute a very
rich database for research. Today, this database is still not exploitable because to make its …
rich database for research. Today, this database is still not exploitable because to make its …
An improved initialization based histogram of K-mean clustering algorithm for hyperchromatic nucleus segmentation in breast carcinoma histopathological images
Mitotic count assessment in breast carcinoma can be a considerable challenge especially
when involve with algorithm development. The challenges lie within the hyperchromatic …
when involve with algorithm development. The challenges lie within the hyperchromatic …
[HTML][HTML] A novel quantitative measurement method for irregular tubules in breast carcinoma
Tubule detection is very crucial and is one of the important criterions for tubule formation
assessment in breast carcinoma. The output of tubule formation is essential to determine the …
assessment in breast carcinoma. The output of tubule formation is essential to determine the …
[HTML][HTML] A Quantitative Measurement Method for Nuclear-Pleomorphism Scoring in Breast Cancer
Abstract Background/Objectives: Nuclear pleomorphism, a crucial determinant of breast
cancer grading under the Nottingham Histopathology Grading (NHG) system, remains …
cancer grading under the Nottingham Histopathology Grading (NHG) system, remains …
Understanding domain knowledge in initialization method for K-mean clustering algorithm in medical images
This work serves as a preliminary study to investigate and identify the applicability of domain
knowledge as an initialization method for K-Mean (KM), typically in medical images. For this …
knowledge as an initialization method for K-Mean (KM), typically in medical images. For this …
Clustering-Based Image Registration of Tubule Candidates in Breast Histopathology Images
Tubule formation is a rudimental and vital parameter to be considered for cancer
aggressiveness detections based on histopathology image data, in accordance with the …
aggressiveness detections based on histopathology image data, in accordance with the …
Simple Landscapes Analysis for Relevant Regions Detection in Breast Carcinoma Histopathological Images
Breast carcinoma represents a huge global health problem among women in both
developed and developing countries. It is estimated that over 508,000 women worldwide …
developed and developing countries. It is estimated that over 508,000 women worldwide …
Textural-Based Discriminant Analysis for Tubule Measurement in Breast Histopathology Images
Tubule formation, one of the core factors determining the overall grade of breast cancer,
relies upon the experience of histopathologists on manual inspection with nuanced decision …
relies upon the experience of histopathologists on manual inspection with nuanced decision …
Segmentation of Relevant Region in Breast Histopathology Images using FCM with Guided Initialization
This study proposes a modified initialization approach for the conventional FCM, namely
FCM with guided initialization. The FCM with guided initialization was implemented to …
FCM with guided initialization. The FCM with guided initialization was implemented to …