Deep multi-view learning methods: A review
Multi-view learning (MVL) has attracted increasing attention and achieved great practical
success by exploiting complementary information of multiple features or modalities …
success by exploiting complementary information of multiple features or modalities …
Translational AI and deep learning in diagnostic pathology
There has been an exponential growth in the application of AI in health and in pathology.
This is resulting in the innovation of deep learning technologies that are specifically aimed at …
This is resulting in the innovation of deep learning technologies that are specifically aimed at …
An enhanced histopathology analysis: An ai-based system for multiclass grading of oral squamous cell carcinoma and segmenting of epithelial and stromal tissue
Simple Summary An established dataset of histopathology images obtained by biopsy and
reviewed by two pathologists is used to create a two-stage oral squamous cell carcinoma …
reviewed by two pathologists is used to create a two-stage oral squamous cell carcinoma …
A systematic review on breast cancer detection using deep learning techniques
Breast cancer is a common health problem in women, with one out of eight women dying
from breast cancer. Many women ignore the need for breast cancer diagnosis as the …
from breast cancer. Many women ignore the need for breast cancer diagnosis as the …
Fusing of deep learning, transfer learning and gan for breast cancer histopathological image classification
MBH Thuy, VT Hoang - … for Knowledge Engineering: Proceedings of the …, 2020 - Springer
Biomedical image classification often deals with limited training sample due to the cost of
labeling data. In this paper, we propose to combine deep learning, transfer learning and …
labeling data. In this paper, we propose to combine deep learning, transfer learning and …
Histological image classification using deep features and transfer learning
A major challenge in the automatic classification of histopathological images is the limited
amount of data available. Supervised learning techniques cannot be applied without some …
amount of data available. Supervised learning techniques cannot be applied without some …
A heteromorphous deep CNN framework for medical image segmentation using local binary pattern
Estimating mitotic nuclei in breast cancer samples can aid in determining the tumor's
aggressiveness and grading system. Because of their strong resemblance to non-mitotic …
aggressiveness and grading system. Because of their strong resemblance to non-mitotic …
Texture features in the Shearlet domain for histopathological image classification
Background A various number of imaging modalities are available (eg, magnetic resonance,
x-ray, ultrasound, and biopsy) where each modality can reveal different structural aspects of …
x-ray, ultrasound, and biopsy) where each modality can reveal different structural aspects of …
Generative adversarial networks for morphological–temporal classification of stem cell images
Frequently, neural network training involving biological images suffers from a lack of data,
resulting in inefficient network learning. This issue stems from limitations in terms of time …
resulting in inefficient network learning. This issue stems from limitations in terms of time …
Searching for Life: End-to-end Automated Detection and Characterization of Ediacaran Biosignatures
With state-of-the-art imaging and analytical tools onboard the NASA Perseverance Rover
Mission, geological information for remote astrobiological analysis is readily available and …
Mission, geological information for remote astrobiological analysis is readily available and …