Deep convolutional neural networks for computer-aided breast cancer diagnostic: a survey
Advances in deep learning networks, especially deep convolutional neural networks
(DCNNs), are causing remarkable breakthroughs in radiology and imaging sciences. These …
(DCNNs), are causing remarkable breakthroughs in radiology and imaging sciences. These …
TTCNN: A breast cancer detection and classification towards computer-aided diagnosis using digital mammography in early stages
Breast cancer is a major research area in the medical image analysis field; it is a dangerous
disease and a major cause of death among women. Early and accurate diagnosis of breast …
disease and a major cause of death among women. Early and accurate diagnosis of breast …
An analytical review on rough set based image clustering
Clustering is one of the most vital image segmentation techniques. However, proper image
clustering has always been a challenging task due to blurred and vague areas near to …
clustering has always been a challenging task due to blurred and vague areas near to …
3D MRI Segmentation using U-Net Architecture for the detection of Brain Tumor
Segmentation of brain tumor from 3D images is one of the most important and difficult tasks
in the field of medical image processing as a manual human-assisted categorization can …
in the field of medical image processing as a manual human-assisted categorization can …
Breast cancer diagnosis using stochastic self-organizing map and enlarge C4. 5
Abstract Timely and accurate Breast Cancer (BC) prediction allows healthcare providers and
doctors to take suitable decisions to treat the patients. Thus, this study employed a strategy …
doctors to take suitable decisions to treat the patients. Thus, this study employed a strategy …
[HTML][HTML] CO2 emission based GDP prediction using intuitionistic fuzzy transfer learning
The industrialization has been the primary cause of the economic boom in almost all
countries. However, this happened at the cost of the environment, as industrialization also …
countries. However, this happened at the cost of the environment, as industrialization also …
A Euclidean distance-based parameter reduction algorithm for interval-valued fuzzy soft sets
H Qin, Y Wang, X Ma, J Wang, C Jiang - Expert Systems with Applications, 2023 - Elsevier
Parameter reduction is a crucial procedure for enhancing the effectiveness of decision-
making processes in the theory of interval-valued fuzzy soft set, which is a developing and …
making processes in the theory of interval-valued fuzzy soft set, which is a developing and …
Suspicious region segmentation using deep features in breast cancer mammogram images
DA Zebari, DA Ibrahim… - … Conference on Computer …, 2022 - ieeexplore.ieee.org
One of the most challenging processes in the image processing field is segmentation,
especially region of the breast and Pectoral Muscle segmentation in mammogram images …
especially region of the breast and Pectoral Muscle segmentation in mammogram images …
Soft hypergraph for modeling global interactions via social media networks
Soft set theory is a map of a set of parameters to the subsets of a universe which can be
utilized to parametrically model the uncertainty. On the other hand, Graph (hypergraph) …
utilized to parametrically model the uncertainty. On the other hand, Graph (hypergraph) …
Development of methods for identifying an appropriate benchmarking peer to establish information security policy
Benchmarking methodology provides organizations with appropriate information security
policy. However, selecting an appropriate organization as a benchmarking peer can be a …
policy. However, selecting an appropriate organization as a benchmarking peer can be a …