[HTML][HTML] The impact of pre-and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
A novel deep-learning model for automatic detection and classification of breast cancer using the transfer-learning technique
Breast cancer (BC) is one of the primary causes of cancer death among women. Early
detection of BC allows patients to receive appropriate treatment, thus increasing the …
detection of BC allows patients to receive appropriate treatment, thus increasing the …
A survey of the recent architectures of deep convolutional neural networks
Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …
which has shown exemplary performance on several competitions related to Computer …
Automated breast cancer detection models based on transfer learning
M Alruwaili, W Gouda - Sensors, 2022 - mdpi.com
Breast cancer is among the leading causes of mortality for females across the planet. It is
essential for the well-being of women to develop early detection and diagnosis techniques …
essential for the well-being of women to develop early detection and diagnosis techniques …
A comprehensive review for breast histopathology image analysis using classical and deep neural networks
Breast cancer is one of the most common and deadliest cancers among women. Since
histopathological images contain sufficient phenotypic information, they play an …
histopathological images contain sufficient phenotypic information, they play an …
A multi-phase deep CNN based mitosis detection framework for breast cancer histopathological images
The mitotic activity index is a key prognostic measure in tumour grading. Microscopy based
detection of mitotic nuclei is a significant overhead and necessitates automation. This work …
detection of mitotic nuclei is a significant overhead and necessitates automation. This work …
Accurate and efficient intracranial hemorrhage detection and subtype classification in 3D CT scans with convolutional and long short-term memory neural networks
In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection
challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed …
challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed …
Review of breast cancer pathologigcal image processing
Y Zhang, KR Xia, CY Li, BL Wei… - BioMed research …, 2021 - Wiley Online Library
Breast cancer is one of the most common malignancies. Pathological image processing of
breast has become an important means for early diagnosis of breast cancer. Using medical …
breast has become an important means for early diagnosis of breast cancer. Using medical …
Breast histopathological image analysis using image processing techniques for diagnostic purposes: A methodological review
Breast cancer in women is the second most common cancer worldwide. Early detection of
breast cancer can reduce the risk of human life. Non-invasive techniques such as …
breast cancer can reduce the risk of human life. Non-invasive techniques such as …