[HTML][HTML] Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward
The recent development in the areas of deep learning and deep convolutional neural
networks has significantly progressed and advanced the field of computer vision (CV) and …
networks has significantly progressed and advanced the field of computer vision (CV) and …
Deep learning on histopathological images for colorectal cancer diagnosis: a systematic review
Colorectal cancer (CRC) is the second most common cancer in women and the third most
common in men, with an increasing incidence. Pathology diagnosis complemented with …
common in men, with an increasing incidence. Pathology diagnosis complemented with …
The future of artificial intelligence in digital pathology–results of a survey across stakeholder groups
Aims Artificial intelligence (AI) provides a powerful tool to extract information from digitised
histopathology whole slide images. During the last 5 years, academic and commercial …
histopathology whole slide images. During the last 5 years, academic and commercial …
Histopathological Analysis for Detecting Lung and Colon Cancer Malignancies Using Hybrid Systems with Fused Features
Lung and colon cancer are among humanity's most common and deadly cancers. In 2020,
there were 4.19 million people diagnosed with lung and colon cancer, and more than 2.7 …
there were 4.19 million people diagnosed with lung and colon cancer, and more than 2.7 …
[HTML][HTML] COVLIAS 1.0 vs. MedSeg: artificial intelligence-based comparative study for automated COVID-19 computed tomography lung segmentation in Italian and …
(1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for
COVID lung severity diagnosis. Earlier proposed approaches during 2020–2021 were …
COVID lung severity diagnosis. Earlier proposed approaches during 2020–2021 were …
Inter-variability study of COVLIAS 1.0: hybrid deep learning models for COVID-19 lung segmentation in computed tomography
Background: For COVID-19 lung severity, segmentation of lungs on computed tomography
(CT) is the first crucial step. Current deep learning (DL)-based Artificial Intelligence (AI) …
(CT) is the first crucial step. Current deep learning (DL)-based Artificial Intelligence (AI) …
A novel Heteromorphous convolutional neural network for automated assessment of tumors in colon and lung histopathology images
The automated assessment of tumors in medical image analysis encounters challenges due
to the resemblance of colon and lung tumors to non-mitotic nuclei and their heteromorphic …
to the resemblance of colon and lung tumors to non-mitotic nuclei and their heteromorphic …
LYSTO: The lymphocyte assessment hackathon and benchmark dataset
We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in
conjunction with the MICCAI 2019 Conference in Shenzhen (China). The competition …
conjunction with the MICCAI 2019 Conference in Shenzhen (China). The competition …
Autonomous Molecular Structure Imaging with High-Resolution Atomic Force Microscopy for Molecular Mixture Discovery
Due to its single-molecule sensitivity, high-resolution atomic force microscopy (HR-AFM) has
proved to be a valuable and uniquely advantageous tool to study complex molecular …
proved to be a valuable and uniquely advantageous tool to study complex molecular …
[HTML][HTML] True-T–Improving T-cell response quantification with holistic artificial intelligence based prediction in immunohistochemistry images
The immune response associated with oncogenesis and potential oncological ther-apeutic
interventions has dominated the field of cancer research over the last decade. T-cell …
interventions has dominated the field of cancer research over the last decade. T-cell …