Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/253106
Title: Design and performance analysis of diffuse optical tomography for sarcoma detection
Researcher: Uma maheswari K
Guide(s): Sathiyamoorthy S
Keywords: Engineering and Technology,Computer Science,Computer Science Information Systems
optical tomography
Sarcoma detection
University: Anna University
Completed Date: 2018
Abstract: Diffuse Optical Tomography is non-invasive, non- ionizing, newlineportable, economical and secured biomedical imaging technique in Nearinfra- newlinered light. This imaging modality promotes the functional imaging of newlinesoft biological tissues namely the brain and breast. The diffuse optical newlinetomography facilitates to reveal the morphological information of fibrous and newlinemuscular tissue lying underneath the blood vessels in brain and breast. The newlineNear-infra-red light ranging (700nm-1000nm) illuminates the brain or breast newlineand the diffuse transmitted light is collected at the tissue surface. newlineIn this thesis, a diffuse optical tomography experimental design newlinewith placement of laser sources and detectors along the tissue boundary are newlinemodeled as forward model. The scattered rays are measured by using newlineavalanche photo-detector signals, since they dominate the tissue medium. newlineThe detector signal is processed to produce the attenuation or the depth of newlinepenetration of the laser source signals in the phantom. The absorption and newlinescattering signals for different tissue volume and area was determined. The newlineoptical flux or fluence rate of the phantom was analyzed in different boundary newlineconditions using boundary element method. Thereby, the soft tissue optical newlineproperty was extracted with diffuse reflectance, which defines the reflectance newlineoutside the tissue boundary. On evaluation of the soft biological tissue optical newlineproperties, based on absorption and scattering coefficient value the normal newlineand cancer patient identification is performed on actual measured data. newline newline
Pagination: xxiii, 166p.
URI: http://hdl.handle.net/10603/253106
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File23.53 kBAdobe PDFView/Open
02_certificates.pdf690.08 kBAdobe PDFView/Open
03_abstract.pdf234.82 kBAdobe PDFView/Open
04_acknowledgment.pdf227.47 kBAdobe PDFView/Open
05_contents.pdf322.09 kBAdobe PDFView/Open
06_chapter1.pdf357.91 kBAdobe PDFView/Open
07_chapter2.pdf374.67 kBAdobe PDFView/Open
08_chapter3.pdf1.03 MBAdobe PDFView/Open
09_chapter4.pdf737.32 kBAdobe PDFView/Open
10_chapter5.pdf1.55 MBAdobe PDFView/Open
11_conclusion.pdf251.04 kBAdobe PDFView/Open
12_references.pdf304.41 kBAdobe PDFView/Open
13_publications.pdf237.32 kBAdobe PDFView/Open
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