Book chapter
Chapter 11 - LOGISMOS-JEI: Segmentation using optimal graph search and just-enough interaction
Handbook of Medical Image Computing and Computer Assisted Intervention, pp.249-272
Elsevier Inc
2020
DOI: 10.1016/B978-0-12-816176-0.00016-8
Abstract
LOGISMOS (Layered Optimal Graph Image Segmentation for Multiple Objects and Surfaces) is a general approach for optimally segmenting multiple n-D surfaces that mutually interact within individual and/or between object. JEI (Just-Enough Interaction) extension enables the users to intuitively and efficiently guide LOGISMOS to achieve clinically acceptable segmentation that still maintains global optimality, embedded shape, and anatomy knowledge. This chapter is aimed at both the conceptual designers of quantitative medical image analysis methods and developers adopting LOGISMOS-JEI to perform new segmentation tasks. The basic principles and essential techniques of LOGISMOS-JEI are presented. Using three clinical segmentation problems, the process of designing LOGISMOS-JEI applications is described with a focus on choosing proper techniques at all stages of the analysis pipeline. The capability of JEI is demonstrated by reporting the achieved segmentation accuracy and quantifying the levels of human effort involved.
Details
- Title: Subtitle
- Chapter 11 - LOGISMOS-JEI: Segmentation using optimal graph search and just-enough interaction
- Creators
- Honghai ZhangKyungmoo LeeZhi ChenSatyananda KashyapMilan Sonka
- Resource Type
- Book chapter
- Publication Details
- Handbook of Medical Image Computing and Computer Assisted Intervention, pp.249-272
- DOI
- 10.1016/B978-0-12-816176-0.00016-8
- Publisher
- Elsevier Inc
- Language
- English
- Date published
- 2020
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; The Iowa Institute for Biomedical Imaging; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984315739402771
Metrics
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