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Whole-sample mapping of cancerous and benign tissue properties

Neary-Zajiczek, L; Essmann, C; Clancy, N; Haider, A; Miranda, E; Shaw, M; Gander, A; ... Stoyanov, D; + view all (2019) Whole-sample mapping of cancerous and benign tissue properties. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. (pp. pp. 760-768). Springer Nature: Cham, Switzerland. Green open access

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Abstract

Structural and mechanical differences between cancerous and healthy tissue give rise to variations in macroscopic properties such as visual appearance and elastic modulus that show promise as signatures for early cancer detection. Atomic force microscopy (AFM) has been used to measure significant differences in stiffness between cancerous and healthy cells owing to its high force sensitivity and spatial resolution, however due to absorption and scattering of light, it is often challenging to accurately locate where AFM measurements have been made on a bulk tissue sample. In this paper we describe an image registration method that localizes AFM elastic stiffness measurements with high-resolution images of haematoxylin and eosin (H&E)-stained tissue to within ±1.5 μ m. Color RGB images are segmented into three structure types (lumen, cells and stroma) by a neural network classifier trained on ground-truth pixel data obtained through k-means clustering in HSV color space. Using the localized stiffness maps and corresponding structural information, a whole-sample stiffness map is generated with a region matching and interpolation algorithm that associates similar structures with measured stiffness values. We present results showing significant differences in stiffness between healthy and cancerous liver tissue and discuss potential applications of this technique.

Type: Proceedings paper
Title: Whole-sample mapping of cancerous and benign tissue properties
Event: 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention
Location: Shenzhen, China
Dates: 13th-17th October 2019
ISBN-13: 978-3-030-32238-0
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-32239-7_84
Publisher version: https://doi.org/10.1007/978-3-030-32239-7_84
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Digital pathology, Whole-slide imaging, Cancer diagnostics, Tissue stiffness
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Surgical Biotechnology
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10087588
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