Multiple instance learning for classifying histopathological images of the breast cancer using residual neural network
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22698
Abstract: Digital histopathological images have complex textures and high variability. Thus, classifying histopathological images requires an accurate classification and recognition of the tissue components in these images. In this article, we propose a novel classification layer… read more here.
Keywords: neural network; network; layer; breast cancer ... See more keywords
Sub-classification of invasive and non-invasive cancer from magnification independent histopathological images using hybrid neural networks
Sign Up to like & getrecommendations! Published in 2021 at "Evolutionary Intelligence"
DOI: 10.1007/s12065-021-00564-3
Abstract: Histopathology plays a crucial role in helping clinicians to manage patient’s health effectively. To improve diagnostic accuracy from histopathology, this study evaluates the potential of the pre-trained deep-learning-based model on a large dataset for discrimination… read more here.
Keywords: histopathological images; cancer; magnification; model ... See more keywords
A hybrid deep learning approach for gland segmentation in prostate histopathological images
Sign Up to like & getrecommendations! Published in 2021 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2021.102076
Abstract: BACKGROUND In digital pathology, the morphology and architecture of prostate glands have been routinely adopted by pathologists to evaluate the presence of cancer tissue. The manual annotations are operator-dependent, error-prone and time-consuming. The automated segmentation… read more here.
Keywords: prostate; segmentation prostate; histopathological images; segmentation ... See more keywords
AI-based Carcinoma Detection and Classification Using Histopathological Images: A Systematic Review
Sign Up to like & getrecommendations! Published in 2022 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2022.105209
Abstract: Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is a subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell carcinoma and adenocarcinoma are two major subtypes of… read more here.
Keywords: review; histopathological images; based carcinoma; detection classification ... See more keywords
Predicting colorectal cancer tumor mutational burden from histopathological images and clinical information using multi-modal deep learning
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac641
Abstract: MOTIVATION Tumor mutational burden (TMB) is an indicator of the efficacy and prognosis of immune checkpoint therapy in colorectal cancer (CRC). Cancer patients with high TMB (TMB_H) values tend to benefit from immunotherapy, whereas those… read more here.
Keywords: multi modal; images clinical; deep learning; histopathological images ... See more keywords
A Convolutional Neural Network and Graph Convolutional Network Based Framework for Classification of Breast Histopathological Images
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3153671
Abstract: The spatial correlation among different tissue components is an essential characteristic for diagnosis of breast cancers based on histopathological images. Graph convolutional network (GCN) can effectively capture this spatial feature representation, and has been successfully… read more here.
Keywords: network; gcn; breast; framework ... See more keywords
Federated Fusion of Magnified Histopathological Images for Breast Tumor Classification in the Internet of Medical Things.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2023.3256974
Abstract: Breast tumor detection and classification on the Internet of Medical Things (IoMT) can be automated with the potential of Artificial Intelligence (AI). However, challenges arise when dealing with sensitive data due to the dependence on… read more here.
Keywords: medical things; breast tumor; classification internet; histopathological images ... See more keywords
TransSurv: Transformer-based Survival Analysis Model Integrating Histopathological Images and Genomic Data for Colorectal Cancer.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2022.3199244
Abstract: Survival analysis is a significant study in cancer prognosis, and the multi-modal data, including histopathological images, genomic data, and clinical information, provides unprecedented opportunities for its development. However, because of the high dimensionality and the… read more here.
Keywords: survival analysis; images genomic; genomic data; histopathological images ... See more keywords
AttentionBoost: Learning What to Attend for Gland Segmentation in Histopathological Images by Boosting Fully Convolutional Networks
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2020.3015198
Abstract: Fully convolutional networks (FCNs) are widely used for instance segmentation. One important challenge is to sufficiently train these networks to yield good generalizations for hard-to-learn pixels, correct prediction of which may greatly affect the success.… read more here.
Keywords: fully convolutional; hard learn; convolutional networks; histopathological images ... See more keywords
Survival prediction of stomach cancer using expression data and deep learning models with histopathological images
Sign Up to like & getrecommendations! Published in 2022 at "Cancer Science"
DOI: 10.1111/cas.15592
Abstract: Accurately predicting patient survival is essential for cancer treatment decision. However, the prognostic prediction model based on histopathological images of stomach cancer patients is still yet to be developed. We propose a deep learning‐based model… read more here.
Keywords: expression data; prediction; histopathological images; cancer ... See more keywords
Classification of Breast Cancer Histopathological Images Using DenseNet and Transfer Learning
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/8904768
Abstract: Breast cancer is one of the most common invading cancers in women. Analyzing breast cancer is nontrivial and may lead to disagreements among experts. Although deep learning methods achieved an excellent performance in classification tasks… read more here.
Keywords: classification; breast; cancer histopathological; breast cancer ... See more keywords