Related Experiment Video
Updated: Jun 15, 2026
05:33
Three-Dimensional Shape Modeling and Analysis of Brain Structures
Published on: November 14, 2019
The brain MR Image segmentation techniques and use of diagnostic packages
Rash Bihari Dubey1, Madasu Hanmandlu, Suresh K Gupta
1Apeejay College of Engineering, ICE Department, Sohna, Gurgaon, India. rbdubeyster@gmail.com
Academic Radiology
|March 10, 2010
Summary
This survey reviews medical image segmentation methods, highlighting automated and semiautomated techniques. These advanced segmentation approaches aid radiologists in faster diagnoses and complement computer-aided diagnosis systems.
Area of Science:
- Medical Imaging
- Biomedical Image Processing
- Radiology
Background:
- Segmentation is crucial for medical image analysis.
- Classification of methods is based on approaches and application domains.
- Computer-aided diagnosis (CAD) is a growing research area in medical imaging.
Purpose of the Study:
- To survey recent segmentation methods in biomedical image processing.
- To critically appraise semiautomated and automated segmentation techniques for anatomical medical images.
- To explore methods for improved medical image segmentation.
Main Methods:
- Literature review of recent segmentation methods.
- Critical appraisal of semiautomated and automated techniques.
- Analysis of methods within the context of Picture Archiving and Communication Systems (PACS).
Main Results:
- Medical image interpretation is shifting from hard-copy to soft-copy studies via PACS.
- Automated segmentation methods assist physicians in rapid diagnosis.
- Semiautomated and automated methods offer distinct advantages and disadvantages.
Conclusions:
- Automated segmentation significantly aids in quick medical diagnoses.
- Computer-aided diagnosis (CAD) serves as a valuable complement to physician expertise.
- Advanced segmentation techniques enhance the efficiency and accuracy of medical image analysis.
