Harini Veeraraghavan

Overview

Best Publications

• Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images

  Duc Fehr;Harini Veeraraghavan;Andreas Wibmer;Tatsuo Gondo

  410
  Citations

• Vision 20/20: Perspectives on automated image segmentation for radiotherapy

  Gregory Sharp;Karl D. Fritscher;Vladimir Pekar;Marta Peroni

  394
  Citations

• Computer vision algorithms for intersection monitoring

  H. Veeraraghavan;O. Masoud;N.P. Papanikolopoulos

  314
  Citations

• GBM Volumetry using the 3D Slicer Medical Image Computing Platform

  Jan Egger;Tina Kapur;Andriy Fedorov;Steve Pieper

  282
  Citations

• Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017.

  Jinzhong Yang;Harini Veeraraghavan;Samuel G. Armato;Keyvan Farahani

  250
  Citations

• Multiple Resolution Residually Connected Feature Streams for Automatic Lung Tumor Segmentation From CT Images

  Jue Jiang;Yu-Chi Hu;Chia-Ju Liu;Darragh Halpenny

  243
  Citations

• Tumor-aware, Adversarial Domain Adaptation from CT to MRI for Lung Cancer Segmentation.

  Jue Jiang;Yu-Chi Hu;Neelam Tyagi;Pengpeng Zhang

  159
  Citations

• Technical note: Extension of CERR for computational radiomics: a comprehensive MATLAB platform for reproducible radiomics research

  Aditya P. Apte;Aditi Iyer;Mireia Crispin-Ortuzar;Mireia Crispin-Ortuzar;Rutu Pandya

  150
  Citations

• Deep learning-based auto-segmentation of targets and organs-at-risk for magnetic resonance imaging only planning of prostate radiotherapy.

  Sharif Elguindi;Michael J. Zelefsky;Jue Jiang;Harini Veeraraghavan

  93
  Citations

• Impact of image preprocessing on the scanner dependence of multi-parametric MRI radiomic features and covariate shift in multi-institutional glioblastoma datasets.

  Hyemin Um;Florent Tixier;Dalton Bermudez;Joseph O Deasy

  91
  Citations

• Patch-based generative adversarial neural network models for head and neck MR-only planning.

  Peter Klages;Ilyes Benslimane;Sadegh Riyahi;Jue Jiang

  77
  Citations

• A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy

  Elizabeth J. Sutton;Natsuko Onishi;Duc A. Fehr;Brittany Z. Dashevsky

  73
  Citations

• Communication Strategies in Multi-robot Search and Retrieval: Experiences with MinDART

  Paul E. Rybski;Amy C. Larson;Harini Veeraraghavan;Monica A. LaPoint

  54
  Citations

• Machine learning-based prediction of microsatellite instability and high tumor mutation burden from contrast-enhanced computed tomography in endometrial cancers.

  Harini Veeraraghavan;Claire F. Friedman;Claire F. Friedman;Deborah F. DeLair;Deborah F. DeLair;Josip Ninčević

  52
  Citations

• Robust target detection and tracking through integration of motion, color, and geometry

  Harini Veeraraghavan;Paul Schrater;Nikos Papanikolopoulos

  50
  Citations

• Reliability of tumor segmentation in glioblastoma: Impact on the robustness of MRI-radiomic features

  Florent Tixier;Hyemin Um;Robert J Young;Harini Veeraraghavan

  39
  Citations

• Classifiers for driver activity monitoring

  Harini Veeraraghavan;Nathaniel Bird;Stefan Atev;Nikolaos Papanikolopoulos

  39
  Citations

• Head and neck cancer patient images for determining auto-segmentation accuracy in T2-weighted magnetic resonance imaging through expert manual segmentations.

  Carlos E. Cardenas;Abdallah S. R. Mohamed;Jinzhong Yang;Mark Gooding

  35
  Citations

• Cross‐modality (CT‐MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets

  Jue Jiang;Yu-Chi Hu;Neelam Tyagi;Pengpeng Zhang

  31
  Citations

• PSIGAN: Joint Probabilistic Segmentation and Image Distribution Matching for Unpaired Cross-Modality Adaptation-Based MRI Segmentation

  Jue Jiang;Yu-Chi Hu;Neelam Tyagi;Andreas Rimner

  15
  Citations