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Harini Veeraraghavan

Showing results (71-80 of 96) with videos related to

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European Radiology|May 21, 2015
Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scoresAndreas Wibmer, Hedvig Hricak, Tatsuo Gondo, et al.
Medical Physics|May 18, 2020
Head and neck cancer patient images for determining auto-segmentation accuracy in T2-weighted magnetic resonance imaging through expert manual segmentationsCarlos E Cardenas, Abdallah S R Mohamed, Jinzhong Yang, et al.
Medical Physics|June 14, 2018
Technical Note: Extension of CERR for computational radiomics: A comprehensive MATLAB platform for reproducible radiomics researchAditya P Apte, Aditi Iyer, Mireia Crispin-Ortuzar, et al.
Cancers|May 13, 2023
Artificial Intelligence in CT and MR Imaging for Oncological ApplicationsRamesh Paudyal, Akash D Shah, Oguz Akin, et al.
European Radiology|December 7, 2016
Differentiation of Uterine Leiomyosarcoma from Atypical Leiomyoma: Diagnostic Accuracy of Qualitative MR Imaging Features and Feasibility of Texture AnalysisYulia Lakhman, Harini Veeraraghavan, Joshua Chaim, et al.
Journal of Medical Imaging (Bellingham, Wash.)|May 6, 2021
Reproducibility of radiomic features using network analysis and its application in Wasserstein <i>k</i>-means clusteringJung Hun Oh, Aditya P Apte, Evangelia Katsoulakis, et al.
European Journal of Radiology|April 1, 2019
Radiogenomics of rectal adenocarcinoma in the era of precision medicine: A pilot study of associations between qualitative and quantitative MRI imaging features and genetic mutationsNatally Horvat, Harini Veeraraghavan, Raphael A Pelossof, et al.
European Radiology|March 15, 2017
A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcomeHebert Alberto Vargas, Harini Veeraraghavan, Maura Micco, et al.
Physics and Imaging in Radiation Oncology|November 8, 2021
Deep learning auto-segmentation and automated treatment planning for trismus risk reduction in head and neck cancer radiotherapyMaria Thor, Aditi Iyer, Jue Jiang, et al.
Neuro-Oncology|October 18, 2019
MRI radiomic features are associated with survival in melanoma brain metastases treated with immune checkpoint inhibitorsAnkush Bhatia, Maxwell Birger, Harini Veeraraghavan, et al.
Pageof 10

Showing results (71-80 of 96) with videos related to

Sort By:
Pageof 10
European Radiology|May 21, 2015
Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scoresAndreas Wibmer, Hedvig Hricak, Tatsuo Gondo, et al.
Medical Physics|May 18, 2020
Head and neck cancer patient images for determining auto-segmentation accuracy in T2-weighted magnetic resonance imaging through expert manual segmentationsCarlos E Cardenas, Abdallah S R Mohamed, Jinzhong Yang, et al.
Medical Physics|June 14, 2018
Technical Note: Extension of CERR for computational radiomics: A comprehensive MATLAB platform for reproducible radiomics researchAditya P Apte, Aditi Iyer, Mireia Crispin-Ortuzar, et al.
Cancers|May 13, 2023
Artificial Intelligence in CT and MR Imaging for Oncological ApplicationsRamesh Paudyal, Akash D Shah, Oguz Akin, et al.
European Radiology|December 7, 2016
Differentiation of Uterine Leiomyosarcoma from Atypical Leiomyoma: Diagnostic Accuracy of Qualitative MR Imaging Features and Feasibility of Texture AnalysisYulia Lakhman, Harini Veeraraghavan, Joshua Chaim, et al.
Journal of Medical Imaging (Bellingham, Wash.)|May 6, 2021
Reproducibility of radiomic features using network analysis and its application in Wasserstein <i>k</i>-means clusteringJung Hun Oh, Aditya P Apte, Evangelia Katsoulakis, et al.
European Journal of Radiology|April 1, 2019
Radiogenomics of rectal adenocarcinoma in the era of precision medicine: A pilot study of associations between qualitative and quantitative MRI imaging features and genetic mutationsNatally Horvat, Harini Veeraraghavan, Raphael A Pelossof, et al.
European Radiology|March 15, 2017
A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcomeHebert Alberto Vargas, Harini Veeraraghavan, Maura Micco, et al.
Physics and Imaging in Radiation Oncology|November 8, 2021
Deep learning auto-segmentation and automated treatment planning for trismus risk reduction in head and neck cancer radiotherapyMaria Thor, Aditi Iyer, Jue Jiang, et al.
Neuro-Oncology|October 18, 2019
MRI radiomic features are associated with survival in melanoma brain metastases treated with immune checkpoint inhibitorsAnkush Bhatia, Maxwell Birger, Harini Veeraraghavan, et al.
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