Mammogram breast cancer CAD systems for mass detection and classification: a review
Although there is an improvement in breast cancer detection and classification (CAD) tools,
there are still some challenges and limitations that need more investigation. The significant …
there are still some challenges and limitations that need more investigation. The significant …
Breast cancer segmentation methods: current status and future potentials
Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …
worldwide as it can help increase the survival rate of patients. Mammograms have been …
Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images
MA Al-Antari, CH Hua, J Bang, S Lee - Applied Intelligence, 2021 - Springer
Abstract Coronavirus disease 2019 (COVID-19) is a novel harmful respiratory disease that
has rapidly spread worldwide. At the end of 2019, COVID-19 emerged as a previously …
has rapidly spread worldwide. At the end of 2019, COVID-19 emerged as a previously …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
Advancements in oncology with artificial intelligence—a review article
Simple Summary With the advancement of artificial intelligence, including machine learning,
the field of oncology has seen promising results in cancer detection and classification …
the field of oncology has seen promising results in cancer detection and classification …
Dual convolutional neural networks for breast mass segmentation and diagnosis in mammography
Deep convolutional neural networks (CNNs) have emerged as a new paradigm for
Mammogram diagnosis. Contemporary CNN-based computer-aided-diagnosis systems …
Mammogram diagnosis. Contemporary CNN-based computer-aided-diagnosis systems …
Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder
Y Jung, T Kim, MR Han, S Kim, G Kim, S Lee… - Scientific Reports, 2022 - nature.com
Discrimination of ovarian tumors is necessary for proper treatment. In this study, we
developed a convolutional neural network model with a convolutional autoencoder (CNN …
developed a convolutional neural network model with a convolutional autoencoder (CNN …
Breast cancer masses classification using deep convolutional neural networks and transfer learning
SA Hassan, MS Sayed, MI Abdalla… - Multimedia Tools and …, 2020 - Springer
With the recent advances in the deep learning field, the use of deep convolutional neural
networks (DCNNs) in biomedical image processing becomes very encouraging. This paper …
networks (DCNNs) in biomedical image processing becomes very encouraging. This paper …
FN-OCT: Disease detection algorithm for retinal optical coherence tomography based on a fusion network
Z Ai, X Huang, J Feng, H Wang, Y Tao… - Frontiers in …, 2022 - frontiersin.org
Optical coherence tomography (OCT) is a new type of tomography that has experienced
rapid development and potential in recent years. It is playing an increasingly important role …
rapid development and potential in recent years. It is playing an increasingly important role …