Radiomics: a primer on high-throughput image phenoty**
Radiomics is a high-throughput approach to image phenoty**. It uses computer
algorithms to extract and analyze a large number of quantitative features from radiological …
algorithms to extract and analyze a large number of quantitative features from radiological …
Prospective clinical research of radiomics and deep learning in oncology: A translational review
Radiomics and deep learning (DL) hold transformative promise and substantial and
significant advances in oncology; however, most methods have been tested in retrospective …
significant advances in oncology; however, most methods have been tested in retrospective …
CT radiomic features of superior mesenteric artery involvement in pancreatic ductal adenocarcinoma: a pilot study
Background Current imaging methods for prediction of complete margin resection (R0) in
patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To …
patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To …
A radiomics‐boosted deep‐learning model for COVID‐19 and non‐COVID‐19 pneumonia classification using chest x‐ray images
Purpose To develop a deep learning model design that integrates radiomics analysis for
enhanced performance of COVID‐19 and non‐COVID‐19 pneumonia detection using chest …
enhanced performance of COVID‐19 and non‐COVID‐19 pneumonia detection using chest …
Radiomics in oncological PET imaging: a systematic review—Part 1, Supradiaphragmatic cancers
Radiomics is an upcoming field in nuclear oncology, both promising and technically
challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia …
challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia …
Clinical application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography radiomics-based machine learning analyses in the field of …
M Nakajo, M **guji, S Ito, A Tani, M Hirahara… - Japanese Journal of …, 2024 - Springer
Abstract Machine learning (ML) analyses using 18F-fluorodeoxyglucose (18F-FDG) positron
emission tomography (PET)/computed tomography (CT) radiomics features have been …
emission tomography (PET)/computed tomography (CT) radiomics features have been …
A systematic review and meta‐analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck …
MM Philip, A Welch, F McKiddie, M Nath - Cancer Medicine, 2023 - Wiley Online Library
Background Positron emission tomography (PET) images of head and neck squamous cell
carcinoma (HNSCC) patients can assess the functional and biochemical processes at …
carcinoma (HNSCC) patients can assess the functional and biochemical processes at …
The role of machine learning in cardiovascular pathology
Abstract Machine learning has seen slow but steady uptake in diagnostic pathology over the
past decade to assess digital whole-slide images. Machine learning tools have incredible …
past decade to assess digital whole-slide images. Machine learning tools have incredible …
Photon counting CT and radiomic analysis enables differentiation of tumors based on lymphocyte burden
The purpose of this study was to investigate if radiomic analysis based on spectral micro-CT
with nanoparticle contrast-enhancement can differentiate tumors based on lymphocyte …
with nanoparticle contrast-enhancement can differentiate tumors based on lymphocyte …
Towards optimal deep fusion of imaging and clinical data via a model‐based description of fusion quality
Background Due to intrinsic differences in data formatting, data structure, and underlying
semantic information, the integration of imaging data with clinical data can be non‐trivial …
semantic information, the integration of imaging data with clinical data can be non‐trivial …