---
abstract: |-
  Medical Image analysis and processing has great
  significance in the field of medicine, especially in Non-
  invasive treatment and clinical study. Medical imaging
  techniques and analysis tools enable the Doctors and
  Radiologists to arrive at a specific diagnosis. Medical Image
  Processing has emerged as one of the most important tools
  to identify as well as diagnose various disorders. Imaging
  helps the Doctors to visualize and analyze the image for
  understanding of abnormalities in internal structures. The
  medical images data obtained from Bio-medical Devices
  which use imaging techniques like Computed Tomography
  (CT), Magnetic Resonance Imaging (MRI) and
  Mammogram, which indicates the presence or absence of
  the lesion along with the patient history, is an important
  factor in the diagnosis. The algorithm proposes the use of
  Digital Image processing tools for the identification of
  Hemorrhage and Infarct in the human brain, by using a
  semi-automatic seeded region growing algorithm for the
  processing of the clinical images. The algorithm has been
  extended to the Real-Time Data of CT brain images and
  uses an intensity-based growing technique to identify the
  infarct and hemorrhage affected area, of the brain. The
  objective of this paper is to propose a seeded region
  growing algorithm to assist the Radiologists in identifying
  the Hemorrhage and Infarct in the human brain and to arrive
  at a decision faster and accurate.ĒLpĪL
altloc: []
chapter: ~
commentary: ~
commref: ~
confdates: ~
conference: ~
confloc: ~
contact_email: ~
creators_id: []
creators_name:
  - family: T
    given: Kesavamurthy
    honourific: ''
    lineage: ''
  - family: S
    given: SubhaRan
    honourific: ''
    lineage: ''
date: 2006
date_type: published
datestamp: 2006-09-01
department: ~
dir: disk0/00/00/50/89
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editors_id: []
editors_name: []
eprint_status: archive
eprintid: 5089
fileinfo: /style/images/fileicons/application_pdf.png;/5089/1/e1.pdf
full_text_status: public
importid: ~
institution: ~
isbn: ~
ispublished: pub
issn: ~
item_issues_comment: []
item_issues_count: 0
item_issues_description: []
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item_issues_reported_by: []
item_issues_resolved_by: []
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item_issues_timestamp: []
item_issues_type: []
keywords: |-
  Biomedical image processing, Hemorrhage, Infarct,
  CT, MRI, Mammogram and lesion
lastmod: 2011-03-11 08:56:34
latitude: ~
longitude: ~
metadata_visibility: show
note: ~
number: 3
pagerange: ~
pubdom: TRUE
publication: Calicut Medical Journal
publisher: Calicut Medical College Alumni Association
refereed: TRUE
referencetext: |-
  [1] Andy Tsai, Anthony Yezzi, Jr., William Wells, Allan Wilsky,
  A Shape based approach to the Segmentation of Medical
  Imagery using Level Sets, IEEE Transactions on Medical
  Imaging., vol. 22, pp. 137-154, February 2003.
  [2] Rishi Rakesh, Probal Chaudhuri, C.A.Murthy, Thresholding
  in Edge Detection: A Statistical Approach, IEEE Transactions
  on Image Processing, vol.13, pp. 927-936, July 2004.
  [3] Cheng-Hung, Wen-Nung Lie, A Downstream Algorithm
  based on Extended Gradient Vector flow field for Object
  Segmentation, IEEE Transactions on Image Processing, vol.
  13, pp. 1379-1392, October 2004.
  [4] Rafael. C. Gonzalez, Richard. E. Woods, Digital Image
  Processing, Addison Wesley, Massachusetts, 1999.
  [5] P.Reimer, Paul M. Parizel, Clinical CT Imaging: A Practical
  Approach, Springer, New York, 2004.
  [6] Paul Suetens, Fundamentals of Medical Imaging, Cambridge
  University Press, London, 2002.
  [7] Lippincott Raven, William E. Erkonen, Wilbur, Radiology:
  the Basics and Fundamentals of Imaging, Lippincott Williams
  & Wilkins, New York, 1998.
  [8] Division of Physiological Imaging, Department of Radiology,
  University of IOWA College of medicine: dpi.radiology
  .uiowa.edu / vida /image/
  [9] Math works worldwide, Matlab Home, Image Processing
  Toolbox, Image Processing, analysis and algorithm
  development: http://www.mathworks.com/products/image
  [10] DICOM Standard, An Introduction to DICOM:
  http://www.psychology.nottingham.ac.uk/staff/cr1/dicom.htm
  [11] Digital Image Processing Lab, Division of Basic Radiological
  Sciences, Department of Radiology, University of Michigan
  Health System: http://www.dipl.rad.med.umich.edu/
relation_type: []
relation_uri: []
reportno: ~
rev_number: 12
series: ~
source: ~
status_changed: 2007-09-12 17:06:53
subjects:
  - calcut
succeeds: ~
suggestions: ~
sword_depositor: ~
sword_slug: ~
thesistype: ~
title: |-
  Research
  Pattern Classification using imaging techniques for Infarct and
  Hemorrhage Identification in the Human Brain
type: journale
userid: 4187
volume: 4