title: The brain MR Image segmentation techniques and use of diagnostic packages.
abstract: OBJECTIVE
  This article provides a survey of segmentation methods for medical images. Usually, classification of segmentation methods is done based on the approaches adopted and the domain of application.
  
  
  METHODS
  This survey is conducted on the recent segmentation methods used in biomedical image processing and explores the methods useful for better segmentation. A critical appraisal of the current status of semiautomated and automated methods is made for the segmentation of anatomical medical images emphasizing the advantages and disadvantages. Computer-aided diagnosis (CAD) used by radiologists as a second opinion has become one of the major research areas in medical imaging and diagnostic radiology. A picture archiving communication system (PACS) is an integrated workflow system for managing images and related data that is designed to streamline operations throughout the whole patient care delivery process.
  
  
  RESULTS
  By using PACS, the medical image interpretation may be changed from conventional hard-copy images to soft-copy studies viewed on the systems workstations.
  
  
  CONCLUSIONS
  The automatic segmentations assist the doctors in making quick diagnosis. The CAD need not be comparable to that of physicians, but is surely complementary.
authors.affiliation: Apeejay College of Engineering, ICE Department, Sohna, Gurgaon, India. rbdubeyster@gmail.com
authors.forename: Rash Bihari
authors.initials: RB
authors.lastname: Dubey
authors.forename: Madasu
authors.initials: M
authors.lastname: Hanmandlu
authors.forename: Suresh K
authors.initials: SK
authors.lastname: Gupta
authors.forename: Sushil K
authors.initials: SK
authors.lastname: Gupta
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007194:India; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011873:Radiology Information Systems; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D013673:Technology Assessment, Biomedical