Discrimination of Tumor Boundary Using Ultrahigh-Resolution Mirau-Based Full-Field Optical Coherent Tomography
Date Issued
2015
Date
2015
Author(s)
Chien, Meng-Ting
Abstract
When doing the cancer surgery to remove the tumor, the only way for physician to get the lesion information is biopsy. But in order to obtain the information from the sample by microscope, the sample preparation is very complicated and time consuming. The advantage of optical coherent tomography (OCT) is that it can get the ultrahigh resolution three-dimensional image in a short time through non-invasive and label-free scanning. In this thesis, we used the OCT system developed by our laboratory to do the research. We used the tissue sample cut from the body to do the previous study of optical biopsy and used the discriminant algorithm to do the research of identification of tumor boundary. The spatial resolutions of the OCT system we use in axial and lateral directions are 0.9 μm and 0.8 μm respectively. In order to overcome the limitation of smaller field of view in OCT system, we use the technique of image stitching to get the large area image. Now, we can get the size of OCT image from 291 μm × 219 μm up to 1 cm × 1 cm. This size is very close to the clinical application and this achievement makes us successfully enter to the research of biopsy. By the advantage of our OCT system, we first got the OCT large area tissue images by scanning the fresh samples which were cut from the living body, including the mouse squamous cell carcinoma and human melanoma. The results in this part all have the distinctive organizational characteristics. We also got the OCT image from the human lymph node tissue, trying to assess the characteristics of cancer metastasis. In order to confirm the credibility of different tissue morphology in OCT images, we have to have the corresponding HE stain images to compare. We tried a lot of sample preparation ways to approach this intent. Finally we chose the unstained paraffin-embedded tissue sections to be the large number of corresponding specimens. For the purpose to enhance the accuracy of interpretation with OCT images, this experiment introduced the concept of computer-aided diagnosis. By corresponding with HE stain images, we obtained the training set from the known tissue type OCT images and used the unknown tissue type OCT images as the test set. Then we extracted the characteristic parameters from both of them and used the linear or quadratic discriminant analysis to identify the tissue type of unknown tissue type region. In this thesis, we successfully developed the discriminant algorithm and program, and also compared the discriminant results under different conditions, like choosing the method of linear or quadratic discriminant analysis, changing the spatial resolution unit or the extracted parameters, or discriminating two or three tissue types. There is the best result in the condition of using the method of linear discriminant analysis to discriminate three tissue types with the spatial resolution unit of 183 μm, and the sensitivity and specificity are up to 0.9998 and 1 respectively.
Subjects
optical coherent tomography
image stitching
optical biopsy
computer-aided diagnosis
linear discriminant analysis
quadratic discriminant analysis
SDGs
Type
thesis
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