Image stitching system with scanning microscopy for histopathological applications

Abstract

Histopathological 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.