[HTML][HTML] Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology

EJ Limkin, R Sun, L Dercle, EI Zacharaki, C Robert… - Annals of …, 2017 - Elsevier
Medical image processing and analysis (also known as Radiomics) is a rapidly growing
discipline that maps digital medical images into quantitative data, with the end goal of …

Radiomics: the process and the challenges

V Kumar, Y Gu, S Basu, A Berglund, SA Eschrich… - Magnetic resonance …, 2012 - Elsevier
“Radiomics” refers to the extraction and analysis of large amounts of advanced quantitative
imaging features with high throughput from medical images obtained with computed …

Validation of a method to compensate multicenter effects affecting CT radiomics

F Orlhac, F Frouin, C Nioche, N Ayache, I Buvat - Radiology, 2019 - pubs.rsna.org
Background Radiomics extracts features from medical images more precisely and more
accurately than visual assessment. However, radiomics features are affected by CT scanner …

The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans

SG Armato III, G McLennan, L Bidaut… - Medical …, 2011 - Wiley Online Library
Purpose: The development of computer‐aided diagnostic (CAD) methods for lung nodule
detection, classification, and quantitative assessment can be facilitated through a well …

[HTML][HTML] Computer-assisted decision support system in pulmonary cancer detection and stage classification on CT images

A Masood, B Sheng, P Li, X Hou, X Wei, J Qin… - Journal of biomedical …, 2018 - Elsevier
Pulmonary cancer is considered as one of the major causes of death worldwide. For the
detection of lung cancer, computer-assisted diagnosis (CADx) systems have been designed …

Changes in CT radiomic features associated with lymphocyte distribution predict overall survival and response to immunotherapy in non–small cell lung cancer

M Khorrami, P Prasanna, A Gupta, P Patil… - Cancer immunology …, 2020 - AACR
No predictive biomarkers can robustly identify patients with non–small cell lung cancer
(NSCLC) who will benefit from immune checkpoint inhibitor (ICI) therapies. Here, in a …

[HTML][HTML] Repeatability and reproducibility study of radiomic features on a phantom and human cohort

AK Jha, S Mithun, V Jaiswar, UB Sherkhane… - Scientific reports, 2021 - nature.com
The repeatability and reproducibility of radiomic features extracted from CT scans need to be
investigated to evaluate the temporal stability of imaging features with respect to a controlled …

Reproducibility and prognosis of quantitative features extracted from CT images

Y Balagurunathan, Y Gu, H Wang, V Kumar… - Translational …, 2014 - Elsevier
We study the reproducibility of quantitative imaging features that are used to describe tumor
shape, size, texture from computed tomography (CT) scans of non-small cell lung cancer …

Parallel deep learning algorithms with hybrid attention mechanism for image segmentation of lung tumors

H Hu, Q Li, Y Zhao, Y Zhang - IEEE Transactions on Industrial …, 2020 - ieeexplore.ieee.org
At present, medical images have played a more and more important role in clinical
treatment. Lung images provide an important reference for doctors to make a diagnosis …

Test–retest data for radiomics feature stability analysis: generalizable or study-specific?

JE van Timmeren, RTH Leijenaar, W van Elmpt… - Tomography, 2016 - mdpi.com
Radiomics is an objective method for extracting quantitative information from medical
images. However, in radiomics, standardization, overfitting, and generalization are major …