List of works - Chintan Parmar

Application of the 3D slicer chest imaging platform segmentation algorithm for large lung nodule delineation

scientific article

Artificial intelligence in radiology

scientific article published on 01 August 2018

Associations Between Somatic Mutations and Metabolic Imaging Phenotypes in Non-Small Cell Lung Cancer

scientific article published on 29 September 2016

Associations between radiologist-defined semantic and automatically computed radiomic features in non-small cell lung cancer

scientific article

Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT

scientific article

Author Correction: Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR.

scientific article

Computational Radiomics System to Decode the Radiographic Phenotype

scientific article

Data Analysis Strategies in Medical Imaging

scholarly article by Chintan Parmar et al published 1 August 2018 in Clinical Cancer Research

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

scientific article

Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging

scientific article published on 22 April 2019

Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR

scientific article

Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study

scientific article published on 30 November 2018

Defining the biological basis of radiomic phenotypes in lung cancer.

scientific article published on 21 July 2017

Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology

scientific article published on 30 March 2016

Impact of experimental design on PET radiomics in predicting somatic mutation status.

scientific article published on 9 October 2017

MO-DE-207B-01: JACK FOWLER JUNIOR INVESTIGATOR COMPETITION WINNER: Between Somatic Mutations and PET-Based Radiomic Features in Non-Small Cell Lung Cancer

article

Machine Learning methods for Quantitative Radiomic Biomarkers

scientific article

Predicting Response to Cancer Immunotherapy using Non-invasive Radiomic Biomarkers

scientific article published on 01 June 2019

Prognostic value of metabolic metrics extracted from baseline positron emission tomography images in non-small cell lung cancer.

scientific article published on 9 September 2013

Radiographic prediction of meningioma grade by semantic and radiomic features

scientific article published on 16 November 2017

Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer.

scientific article

Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer

scientific article

Radiomics of Coronary Artery Calcium in the Framingham Heart Study

scientific article published on 27 February 2020

Robust Radiomics feature quantification using semiautomatic volumetric segmentation

scientific article

Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancer.

scientific article published on 31 May 2017

Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability

scientific article

List of works by Chintan Parmar

Application of the 3D slicer chest imaging platform segmentation algorithm for large lung nodule delineation

Artificial intelligence in radiology

Associations Between Somatic Mutations and Metabolic Imaging Phenotypes in Non-Small Cell Lung Cancer

Associations between radiologist-defined semantic and automatically computed radiomic features in non-small cell lung cancer

Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT

Author Correction: Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR.

Computational Radiomics System to Decode the Radiographic Phenotype

Data Analysis Strategies in Medical Imaging

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging

Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR

Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study

Defining the biological basis of radiomic phenotypes in lung cancer.

Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology

Impact of experimental design on PET radiomics in predicting somatic mutation status.

MO-DE-207B-01: JACK FOWLER JUNIOR INVESTIGATOR COMPETITION WINNER: Between Somatic Mutations and PET-Based Radiomic Features in Non-Small Cell Lung Cancer

Machine Learning methods for Quantitative Radiomic Biomarkers

Predicting Response to Cancer Immunotherapy using Non-invasive Radiomic Biomarkers

Prognostic value of metabolic metrics extracted from baseline positron emission tomography images in non-small cell lung cancer.

Radiographic prediction of meningioma grade by semantic and radiomic features

Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer.

Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer

Radiomics of Coronary Artery Calcium in the Framingham Heart Study

Robust Radiomics feature quantification using semiautomatic volumetric segmentation

Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancer.

Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability