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HYPERSPECTRAL OPTICAL IMAGING
FOR DETECTION, DIAGNOSIS AND STAGING OF CANCER
by
Anika Otamu Naomi Joseph
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOMEDICAL ENGINEERING)
May 2012
Copyright 2012 Anika Otamu Naomi Joseph
Object Description
| Title | Hyperspectral optical imaging for detection, diagnosis and staging of cancer |
| Author | Joseph, Anika Otamu Naomi |
| Author email | anikajos@usc.edu;anika.joseph@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Biomedical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2012-01-17 |
| Date submitted | 2012-05-15 |
| Date approved | 2012-05-15 |
| Restricted until | 2012-05-15 |
| Date published | 2012-05-15 |
| Advisor (committee chair) |
Khoo, Michael C.K. Farkas, Daniel L. |
| Advisor (committee member) |
D'Argenio, David Pinkston, Timothy Singh, Manbir |
| Abstract | The American Cancer Society estimates that in 2012 about 577,190 people will die of cancer in the United States (US). It is estimated that in 2012, 1,638, 910 people will be diagnosed with cancer, which remains the second most common cause of death in the US. NIH estimates from 2007 put the overall cost of cancer that year as $226.8 billion in direct and indirect costs. This dissertation explored selected cancers, focusing on women’s cancers: breast, cervical, melanoma (which has higher incidence and incidence increase in women); and new investigational approaches for translational research using optical imaging and image processing techniques. It is well known that the established criteria for cytology and even histopathology, long considered the gold standard for diagnosis, are subjective and suffer from difficulties with interpretation. ❧ This dissertation contains a step wise progression of in situ and in vivo approaches to various challenges in pathology applications towards a proposed combination of multi-spectral imaging methods and image analysis techniques to create a prototype automated computer-aided system towards the diagnosis of cancer using digitized multispectral slides. The techniques have been applied to many areas from fresh stained and unstained breast tissue to in vivo imaging of lesions suspected to be melanoma. There are several original contributions: first, a quantitative assessment of the utility of various multispectral devices and imagery for segmentation and classification tasks in pathology. Next, tissue level and object level segmentation algorithms are developed for various histological classes along with quantitative metrics. In addition, references of both tissue, spatial, and object level features are extracted to create a comprehensive feature selection framework for classification of objects and images. The tools, algorithms, and methods described are for quantifying molecular changes in light microscope images of cellular structures indicative of cancer or precancerous lesions. ❧ For the cervical and melanoma applications object level features as implemented are versatile and useful to extract important features even from relatively inaccurately segmented images. In addition, the use of non-nuclear features, like features of the cytoplasm and stroma has very good classification performance when compared to commercial devices. The system is in two parts: the segmentation of squamous epithelium and the sub-sequent diagnosis of CIN. For the segmentation of squamous epithelium, to save processing time, a multi-resolution method is developed to segment cervical virtual slides. ❧ The nuclei segmentation method uses robust texture features in combination with a Support Vector Machine (SVM) to perform classification. Medical histology rules are finally applied to remove misclassifications. In tests using 31 virtual slides, the segmentation achieves an average accuracy of more than 94.25%. Training nuclei are spectrally classified into Normal, CIN I, CIN II and CIN III. The final diagnosis for a slide region is based on combining the classification of nuclei and classical morphologic features. The robustness of the system in terms of regional diagnosis is measured against slides manually classified by three pathologists. Results indicate that the multispectral imaging system offers a promising basis for a computer-assisted diagnostic tool. Its main limitation is seen to be in the selection of more extensive and more varied training data. |
| Keyword | hyperspectral; imaging; breast; melanoma; image processing; pattern recognition; cervical intra-epithelial neoplasia; pap smear |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Rights | Joseph, Anika Otamu Naomi |
| Access conditions | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@usc.edu |
| Archival file | uscthesesreloadpub_Volume4/etd-JosephAnik-851.pdf |
Description
| Title | Page 1 |
| Full text | HYPERSPECTRAL OPTICAL IMAGING FOR DETECTION, DIAGNOSIS AND STAGING OF CANCER by Anika Otamu Naomi Joseph A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (BIOMEDICAL ENGINEERING) May 2012 Copyright 2012 Anika Otamu Naomi Joseph |
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