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Title: Classification of Mammograms and DW T based Detection of Microcalcification
Researcher: Mini M G
Guide(s): Dr Tessamma Thomas
Keywords: Breast Cancer
Digital Image Processing
Medical Image Processing
Neural Network
The Wavelet Transform
Tools for image processing
Upload Date: 21-Aug-2014
University: Cochin University of Science and Technology
Completed Date: 14/07/2004
Abstract: The presence of clustered microcalcifications is one of the most important and newlinesometimes the only sign of cancer on a mammogram WT based techniques are applied on the remaining mammograms those are obviously newlineabnormal to detect possible microcalcifications The goal of this work is to improve the newlinedetection performance and throughput of screening mammography thus providing a newlinesecond opinion to the radiologists The state of the art DWT computation algorithms are not suitable for practical newlineapplications with memory and delay constraints as it is not a block transfon Hence in newlinethis work the development of a Block DWT computational structure having newlinelow processing memory requirement has also been taken up newline
Appears in Departments:Department of Electronics

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01_title.pdfAttached File16.55 kBAdobe PDFView/Open
02_dedication.pdf40.35 kBAdobe PDFView/Open
03_certificate.pdf46.65 kBAdobe PDFView/Open
04_declaration.pdf44.5 kBAdobe PDFView/Open
05_acknowledgement.pdf56.04 kBAdobe PDFView/Open
06_contents.pdf77.61 kBAdobe PDFView/Open
07_list of figures.pdf70.72 kBAdobe PDFView/Open
08_list of tables.pdf54.35 kBAdobe PDFView/Open
09_abbreviations.pdf65.38 kBAdobe PDFView/Open
10_chapter 1.pdf280.32 kBAdobe PDFView/Open
11_chapter 2.pdf236.76 kBAdobe PDFView/Open
12_chapter 3.pdf4.11 MBAdobe PDFView/Open
13_chapter 4.pdf549.16 kBAdobe PDFView/Open
14_chapter 5.pdf1.47 MBAdobe PDFView/Open
15_chapter 6.pdf2.58 MBAdobe PDFView/Open
16_chapter 7.pdf1.3 MBAdobe PDFView/Open
17_chapter 8.pdf82.11 kBAdobe PDFView/Open
mini.pdf10.92 MBAdobe PDFView/Open

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