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AuthorQidwai, Uvais
AuthorAkbar, Muhammad Ali
Available date2021-06-20T06:10:58Z
Publication Date2016
Publication NameIECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences
ResourceScopus
URIhttp://dx.doi.org/10.1109/IECBES.2016.7843505
URIhttp://hdl.handle.net/10576/20706
AbstractHistopathological analysis of biopsy or surgical specimen is a common clinical practice for diagnostic purposes. Essentially, the process involves slicing the biopsy or surgical sample into very thin slices, placing them on glass slides and viewing them under microscopes. Predominantly, the placement, positioning, and view control is done manually by the pathologists in most of the clinics and hospitals because of which the diagnosis remains heavily dependents upon the experience and performance of the pathologist. Moreover, the slide scanning relies predominantly on the slide placement accuracy. A misaligned slide will create misaligned images which can either miss out information or have blank artifacts due to image frame placement methodology. In this paper, a simple 'add-on' system has been presented that can be used to scan single slide with moderate speed and produces the image on a Virtual reality headset to provide the submerged feeling. Most importantly, it utilizes advanced image stitching algorithms to align the frames from the captured video stream of the slide to produce a very accurate image with a very large size. The stitching is done using the standard feature-based algorithms which have been modified in this work by incorporating affine blending maps to combine the features into final image. It has been found that the image stitching algorithm provides the stitched image with less than 2% error for the given test images.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectAffine transformation
computer vision
Image blending
RANSAC
Slide scanning system
SURF
TitleImage stitching system with scanning microscopy for histopathological applications
TypeConference Paper
Pagination522-527
dc.accessType Abstract Only


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