Imaging as a surrogate for the early prediction and assessment of treatment response through the analysis of 4-D texture ensembles (ISEPARATE)

Peter Maday, Parmeshwar Khurd, Lance Ladic, Mitchell Schnall, Mark Rosen, Christos Davatzikos, Ali Kamen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In order to facilitate the use of imaging as a surrogate endpoint for the early prediction and assessment of treatment response, we present a quantitative image analysis system to process the anatomical and functional images acquired over the course of treatment. The key features of our system are deformable registration, texture analysis via texton histograms, feature selection using the minimal-redundancy-maximal-relevance method, and classification using support vector machines. The objective of the proposed image analysis and machine learning methods in our system is to permit the identification of multi-parametric imaging phenotypic properties that have superior diagnostic and prognostic value as compared to currently used morphometric measurements. We evaluate our system for predicting treatment response of breast cancer patients undergoing neoadjuvant chemotherapy using a series of MRI acquisitions.

Original languageEnglish (US)
Title of host publicationMedical Computer Vision
Subtitle of host publicationRecognition Techniques and Applications in Medical Imaging - International MICCAI Workshop, MCV 2010, Revised Selected Papers
Pages164-173
Number of pages10
DOIs
StatePublished - Feb 21 2011
EventWorkshop on Medical Computer Vision, MCV 2010, Held in Conjunction with the 13th International Conference on Medical Image Computing and Computer - Assisted Intervention, MICCAI 2010 - Beijing, China
Duration: Sep 20 2010Sep 20 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6533 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherWorkshop on Medical Computer Vision, MCV 2010, Held in Conjunction with the 13th International Conference on Medical Image Computing and Computer - Assisted Intervention, MICCAI 2010
CountryChina
CityBeijing
Period9/20/109/20/10

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Keywords

  • image registration
  • texture classification
  • therapy response

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Maday, P., Khurd, P., Ladic, L., Schnall, M., Rosen, M., Davatzikos, C., & Kamen, A. (2011). Imaging as a surrogate for the early prediction and assessment of treatment response through the analysis of 4-D texture ensembles (ISEPARATE). In Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging - International MICCAI Workshop, MCV 2010, Revised Selected Papers (pp. 164-173). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6533 LNCS). https://doi.org/10.1007/978-3-642-18421-5_16