Work

Extended depth of field imaging for mosaic hyperspectral images

Year: 2023

Type: conference-paper

Abstract: Hyperspectral imaging (HSI) is an emerging modality for digital pathology. The purpose of this study is to develop an extended depth of field (EDOF) method for mosaic hyperspectral images acquired with a snapshot camera. EDOF is a technique for ensuring that an image is in focus at all points. A stack of mosaicked hyperspectral images of hematoxylin and eosin (H&E)-stained histologic slides were acquired at different positions along the z-axis and used to output a hyperspectral histologic image that was in-focus at every point. Three different methods were compared to achieve a fully focused image. We compared conventional patch-based methods to our proposed growth-based and band-based methods. The Brenner function was used to quantitatively measure the focus quality of each image measured. The results show that both of our proposed methods performed better qualitatively and quantitatively than the patch-based method, with the band-based method performing the best, as it leveraged dividing pixels into their proper wavelengths in addition to spatially, giving the algorithm better contrast to measure. In terms of speed, the band-based method was the fastest, followed by the patch-based method, with the growth-based method being the slowest. Our proposed extended depth of field hyperspectral imaging methods can have immediate applications in digital pathology, especially whole slide imaging, and other microscopic imaging.

Source: SPIE Medical Imaging: Digital and Computational Pathology

DOI: 10.1117/12.2653923

Authors: Armand Rathgeb, Ling Ma, Minh H. Tran, Baowei Fei

Institutions: The University of Texas at Dallas, The University of Texas Southwestern Medical Center

Language: English

Topic: Advanced Image Fusion Techniques

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: Cancer Prevention and Research Institute of Texas, National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute

Awards: Image-guided Intravascular Robotic System for Mitral Valve Repair and Implants, MOLECULAR IMAGING DIRECTED, 3D ULTRASOUND-GUIDED, BIOPSY SYSTEM, STAN-CT: Standardization and Normalization of CT images for Lung Cancer Patients, ACADEMIC-INDUSTRIAL PARTNERSHIP FOR TRANSLATION OF PET/TRUS GUIDED INTERVENTION, Smart Surgical Microscope Powered by AI Technology and Hyperspectral Imaging