Results 71 to 80 of about 71,655 (241)
EJNMMI Research, 2023 Background Vertebral compression fractures (VCFs) are common clinical problems that arise from various reasons. The differential diagnosis of benign and malignant VCFs is challenging.
Xun Wang +8 more
doaj +1 more source
Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer
, 2017 Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics is foreseen as an essential prognostic tool for cancer risk assessment and the quantification of intratumoural heterogeneity. In this
Aerts, Hugo J. W. L. +11 more
core +2 more sources
Radiomics in Oncology: A Practical Guide
Radiographics, 2021 Radiomics refers to the extraction of mineable data from medical imaging and has been applied within oncology to improve diagnosis, prognostication, and clinical decision support, with the goal of delivering precision medicine.
J. Shur +9 more
semanticscholar +1 more source
Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images [PDF]
, 2018 Breast cancer is one of the most common types of cancer and leading cancer-related death causes for women. In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology Images, we compare one handcrafted feature extractor and five transfer ...
FA Spanhol +8 more
core +3 more sources
Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rays [PDF]
arXiv, 2022 Before the recent success of deep learning methods for automated medical image analysis, practitioners used handcrafted radiomic features to quantitatively describe local patches of medical images. However, extracting discriminative radiomic features relies on accurate pathology localization, which is difficult to acquire in real-world settings ...
arxiv
Frontiers in Oncology, 2022 ObjectivesTo construct a contrast-enhanced CT-based radiomics nomogram that combines clinical factors and a radiomics signature to distinguish papillary renal cell carcinoma (pRCC) type 1 from pRCC type 2 tumours.MethodsA total of 131 patients with 60 in
Yankun Gao +10 more
doaj +1 more source
The Bionic Radiologist: avoiding blurry pictures and providing greater insights [PDF]
, 2019 Radiology images and reports have long been digitalized. However, the potential of the more than 3.6 billion radiology examinations performed annually worldwide has largely gone unused in the effort to digitally transform health care.
Dewey, Marc, Wilkens, Uta
core +1 more source
Radiomics-Informed Deep Learning for Classification of Atrial Fibrillation Sub-Types from Left-Atrium CT Volumes [PDF]
arXiv, 2023 Atrial Fibrillation (AF) is characterized by rapid, irregular heartbeats, and can lead to fatal complications such as heart failure. The disease is divided into two sub-types based on severity, which can be automatically classified through CT volumes for disease screening of severe cases.
arxiv
MPRAD: A Multiparametric Radiomics Framework [PDF]
Breast Cancer Res Treat (2020), 2018 Multiparametric radiological imaging is vital for detection, characterization and diagnosis of many different diseases. The use of radiomics for quantitative extraction of textural features from radiological imaging is increasing moving towards clinical decision support.
arxiv +1 more source
Insights into ImagingPurpose To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. Methods We conducted an online modified Delphi study with a group of international experts.
Burak Koçak +59 more
semanticscholar +1 more source