Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners

M. Asjid Tanveer; Wajahat Nawaz; Haroon Rashid; Amber Kiyani; Syed Ali Khurram; Hassan Aqeel Khan

doi:10.1109/EMBC.2019.8857765

Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners

M. Asjid Tanveer, Wajahat Nawaz, Haroon Rashid, Amber Kiyani, Syed Ali Khurram, Hassan Aqeel Khan^*

^*Corresponding author for this work

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Automated analysis of digitized pathology images in tele-health applications can have a transformative impact on under-served communities in the developing world. However, the vast majority of existing image analysis algorithms are trained on slide images acquired via expensive Whole-Slide-Imaging (WSI) scanners. High scanner cost is a key bottleneck preventing large-scale adoption of digital pathology in developing countries. In this work, we investigate the viability of automated analysis of slide images captured from the eyepiece of a microscope via a smart phone. The mitosis detection application is considered as a use case.Results indicate performance degradation when using (lower-quality) smartphone images; as expected. However, the performance gap is not too wide (F1-score smartphone=0.65, F1-score WSI=0.70) demonstrating that smartphones could potentially be employed as image acquisition devices for digital pathology at locations where expensive scanners are not available.

Original language	English
Title of host publication	2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Publisher	IEEE
Pages	4462-4465
Number of pages	4
ISBN (Electronic)	9781538613115
DOIs	https://doi.org/10.1109/EMBC.2019.8857765
Publication status	Published - 23 Jul 2019
Event	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany Duration: 23 Jul 2019 → 27 Jul 2019

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Country/Territory	Germany
City	Berlin
Period	23/07/19 → 27/07/19

Bibliographical note

Funding Information:
This work was generously supported NVIDIA Corporation's GPU grant program. The authors are grateful to NVIDIA for donating a TitanX GPU to support our research.

Keywords

Health Informatics
Histopathological imaging informatics
Imaging Informatics
Mobile health
Sensor Informatics
Sensor-based mHealth applications

Access to Document

10.1109/EMBC.2019.8857765

Cite this

Tanveer, M. A., Nawaz, W., Rashid, H., Kiyani, A., Khurram, S. A., & Khan, H. A. (2019). Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 (pp. 4462-4465). Article 8857765 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). IEEE. https://doi.org/10.1109/EMBC.2019.8857765

Tanveer, M. Asjid ; Nawaz, Wajahat ; Rashid, Haroon et al. / Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. IEEE, 2019. pp. 4462-4465 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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title = "Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners",

abstract = "Automated analysis of digitized pathology images in tele-health applications can have a transformative impact on under-served communities in the developing world. However, the vast majority of existing image analysis algorithms are trained on slide images acquired via expensive Whole-Slide-Imaging (WSI) scanners. High scanner cost is a key bottleneck preventing large-scale adoption of digital pathology in developing countries. In this work, we investigate the viability of automated analysis of slide images captured from the eyepiece of a microscope via a smart phone. The mitosis detection application is considered as a use case.Results indicate performance degradation when using (lower-quality) smartphone images; as expected. However, the performance gap is not too wide (F1-score smartphone=0.65, F1-score WSI=0.70) demonstrating that smartphones could potentially be employed as image acquisition devices for digital pathology at locations where expensive scanners are not available.",

keywords = "Health Informatics, Histopathological imaging informatics, Imaging Informatics, Mobile health, Sensor Informatics, Sensor-based mHealth applications",

author = "Tanveer, {M. Asjid} and Wajahat Nawaz and Haroon Rashid and Amber Kiyani and Khurram, {Syed Ali} and Khan, {Hassan Aqeel}",

note = "Funding Information: This work was generously supported NVIDIA Corporation's GPU grant program. The authors are grateful to NVIDIA for donating a TitanX GPU to support our research. ; 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 ; Conference date: 23-07-2019 Through 27-07-2019",

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doi = "10.1109/EMBC.2019.8857765",

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Tanveer, MA, Nawaz, W, Rashid, H, Kiyani, A, Khurram, SA & Khan, HA 2019, Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners. in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019., 8857765, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, IEEE, pp. 4462-4465, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, Berlin, Germany, 23/07/19. https://doi.org/10.1109/EMBC.2019.8857765

Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners. / Tanveer, M. Asjid; Nawaz, Wajahat; Rashid, Haroon et al.
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. IEEE, 2019. p. 4462-4465 8857765 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Published conference output › Conference publication

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T1 - Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners

AU - Tanveer, M. Asjid

AU - Nawaz, Wajahat

AU - Rashid, Haroon

AU - Kiyani, Amber

AU - Khurram, Syed Ali

AU - Khan, Hassan Aqeel

N1 - Funding Information: This work was generously supported NVIDIA Corporation's GPU grant program. The authors are grateful to NVIDIA for donating a TitanX GPU to support our research.

PY - 2019/7/23

Y1 - 2019/7/23

N2 - Automated analysis of digitized pathology images in tele-health applications can have a transformative impact on under-served communities in the developing world. However, the vast majority of existing image analysis algorithms are trained on slide images acquired via expensive Whole-Slide-Imaging (WSI) scanners. High scanner cost is a key bottleneck preventing large-scale adoption of digital pathology in developing countries. In this work, we investigate the viability of automated analysis of slide images captured from the eyepiece of a microscope via a smart phone. The mitosis detection application is considered as a use case.Results indicate performance degradation when using (lower-quality) smartphone images; as expected. However, the performance gap is not too wide (F1-score smartphone=0.65, F1-score WSI=0.70) demonstrating that smartphones could potentially be employed as image acquisition devices for digital pathology at locations where expensive scanners are not available.

AB - Automated analysis of digitized pathology images in tele-health applications can have a transformative impact on under-served communities in the developing world. However, the vast majority of existing image analysis algorithms are trained on slide images acquired via expensive Whole-Slide-Imaging (WSI) scanners. High scanner cost is a key bottleneck preventing large-scale adoption of digital pathology in developing countries. In this work, we investigate the viability of automated analysis of slide images captured from the eyepiece of a microscope via a smart phone. The mitosis detection application is considered as a use case.Results indicate performance degradation when using (lower-quality) smartphone images; as expected. However, the performance gap is not too wide (F1-score smartphone=0.65, F1-score WSI=0.70) demonstrating that smartphones could potentially be employed as image acquisition devices for digital pathology at locations where expensive scanners are not available.

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KW - Mobile health

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KW - Sensor-based mHealth applications

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ER -

Tanveer MA, Nawaz W, Rashid H, Kiyani A, Khurram SA, Khan HA. Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. IEEE. 2019. p. 4462-4465. 8857765. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2019.8857765

Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners

Abstract

Publication series

Conference

Bibliographical note

Keywords

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