[HTML][HTML] Radiomics in medical imaging—“how-to” guide and critical reflection
JE Van Timmeren, D Cester, S Tanadini-Lang… - Insights into …, 2020 - Springer
Radiomics is a quantitative approach to medical imaging, which aims at enhancing the
existing data available to clinicians by means of advanced mathematical analysis. Through …
existing data available to clinicians by means of advanced mathematical analysis. Through …
[HTML][HTML] A deep look into radiomics
C Scapicchio, M Gabelloni, A Barucci, D Cioni… - La radiologia …, 2021 - Springer
Radiomics is a process that allows the extraction and analysis of quantitative data from
medical images. It is an evolving field of research with many potential applications in …
medical images. It is an evolving field of research with many potential applications in …
Well-aerated lung on admitting chest CT to predict adverse outcome in COVID-19 pneumonia
D Colombi, FC Bodini, M Petrini, G Maffi, N Morelli… - Radiology, 2020 - pubs.rsna.org
Background CT of patients with severe acute respiratory syndrome coronavirus 2 disease
depicts the extent of lung involvement in coronavirus disease 2019 (COVID-19) pneumonia …
depicts the extent of lung involvement in coronavirus disease 2019 (COVID-19) pneumonia …
[HTML][HTML] TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning
Background and ObjectiveProcessing of medical images such as MRI or CT presents
different challenges compared to RGB images typically used in computer vision. These …
different challenges compared to RGB images typically used in computer vision. These …
A review in radiomics: making personalized medicine a reality via routine imaging
J Guiot, A Vaidyanathan, L Deprez… - Medicinal research …, 2022 - Wiley Online Library
Radiomics is the quantitative analysis of standard‐of‑care medical imaging; the information
obtained can be applied within clinical decision support systems to create diagnostic …
obtained can be applied within clinical decision support systems to create diagnostic …
Machine and deep learning methods for radiomics
Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale
extracted imaging information to clinical and biological endpoints. The development of …
extracted imaging information to clinical and biological endpoints. The development of …
Deep learning predicts lung cancer treatment response from serial medical imaging
Purpose: Tumors are continuously evolving biological systems, and medical imaging is
uniquely positioned to monitor changes throughout treatment. Although qualitatively tracking …
uniquely positioned to monitor changes throughout treatment. Although qualitatively tracking …
[HTML][HTML] Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor …
Background: in current clinical practice, the standard evaluation for axillary lymph node
(ALN) status in breast cancer has a low efficiency and is based on an invasive procedure …
(ALN) status in breast cancer has a low efficiency and is based on an invasive procedure …
Computational radiomics system to decode the radiographic phenotype
Radiomics aims to quantify phenotypic characteristics on medical imaging through the use
of automated algorithms. Radiomic artificial intelligence (AI) technology, either based on …
of automated algorithms. Radiomic artificial intelligence (AI) technology, either based on …
[HTML][HTML] ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset
MR Hernandez Petzsche, E de la Rosa, U Hanning… - Scientific data, 2022 - nature.com
Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer
based automated medical image processing is increasingly finding its way into clinical …
based automated medical image processing is increasingly finding its way into clinical …