Reliable oral cancer classification framework with Bayesian deep learning

Bofan Song; Sumsum Sunny; Shaobai Li; G. Keerthi; Sanjana Patrick; Nirza Mukhia; Shubha Gurudath; Subhashini Raghavan; Pramila Mendonca; Tsusennaro; Shirley T. Leivon; Trupti Kolur; Vivek Shetty; R. Vidya Bushan; Rohan Ramesh; Vijay Pillai; Alben Sigamani; Amritha Suresh; moni Abraham Kuriakose; Praveen Birur; Rongguang Liang

doi:10.1364/FIO.2020.JM6B.18

Reliable oral cancer classification framework with Bayesian deep learning

Bofan Song, Sumsum Sunny, Shaobai Li, G. Keerthi, Sanjana Patrick, Nirza Mukhia, Shubha Gurudath, Subhashini Raghavan, Pramila Mendonca, Tsusennaro, Shirley T. Leivon, Trupti Kolur, Vivek Shetty, R. Vidya Bushan, Rohan Ramesh, Vijay Pillai, Alben Sigamani, Amritha Suresh, moni Abraham Kuriakose, Praveen BirurRongguang Liang

Optical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Standard deep learning algorithms for clinical image classification are unable to understand their confidence in a decision. We developed a Bayesian deep network could estimate uncertainty to assess the reliability of oral cancer image classification.

Original language	English (US)
Title of host publication	Frontiers in Optics - Proceedings Frontiers in Optics / Laser Science, Part of Frontiers in Optics + Laser Science APS/DLS, FiO 2020
Publisher	Optica Publishing Group (formerly OSA)
ISBN (Electronic)	9781943580804
DOIs	https://doi.org/10.1364/FIO.2020.JM6B.18
State	Published - Sep 14 2020
Event	2020 Frontiers in Optics Conference, FiO 2020 - Washington, United States Duration: Sep 14 2020 → Sep 17 2020

Publication series

Name	Optics InfoBase Conference Papers
ISSN (Electronic)	2162-2701

Conference

Conference	2020 Frontiers in Optics Conference, FiO 2020
Country/Territory	United States
City	Washington
Period	9/14/20 → 9/17/20

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Mechanics of Materials

Access to Document

10.1364/FIO.2020.JM6B.18

Cite this

Song, B., Sunny, S., Li, S., Keerthi, G., Patrick, S., Mukhia, N., Gurudath, S., Raghavan, S., Mendonca, P., Tsusennaro, Leivon, S. T., Kolur, T., Shetty, V., Vidya Bushan, R., Ramesh, R., Pillai, V., Sigamani, A., Suresh, A., Kuriakose, M. A., ... Liang, R. (2020). Reliable oral cancer classification framework with Bayesian deep learning. In Frontiers in Optics - Proceedings Frontiers in Optics / Laser Science, Part of Frontiers in Optics + Laser Science APS/DLS, FiO 2020 Article JM6B.18 (Optics InfoBase Conference Papers). Optica Publishing Group (formerly OSA). https://doi.org/10.1364/FIO.2020.JM6B.18

Reliable oral cancer classification framework with Bayesian deep learning. / Song, Bofan; Sunny, Sumsum; Li, Shaobai et al.
Frontiers in Optics - Proceedings Frontiers in Optics / Laser Science, Part of Frontiers in Optics + Laser Science APS/DLS, FiO 2020. Optica Publishing Group (formerly OSA), 2020. JM6B.18 (Optics InfoBase Conference Papers).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Song, B, Sunny, S, Li, S, Keerthi, G, Patrick, S, Mukhia, N, Gurudath, S, Raghavan, S, Mendonca, P, Tsusennaro, Leivon, ST, Kolur, T, Shetty, V, Vidya Bushan, R, Ramesh, R, Pillai, V, Sigamani, A, Suresh, A, Kuriakose, MA, Birur, P & Liang, R 2020, Reliable oral cancer classification framework with Bayesian deep learning. in Frontiers in Optics - Proceedings Frontiers in Optics / Laser Science, Part of Frontiers in Optics + Laser Science APS/DLS, FiO 2020., JM6B.18, Optics InfoBase Conference Papers, Optica Publishing Group (formerly OSA), 2020 Frontiers in Optics Conference, FiO 2020, Washington, United States, 9/14/20. https://doi.org/10.1364/FIO.2020.JM6B.18

Song B, Sunny S, Li S, Keerthi G, Patrick S, Mukhia N et al. Reliable oral cancer classification framework with Bayesian deep learning. In Frontiers in Optics - Proceedings Frontiers in Optics / Laser Science, Part of Frontiers in Optics + Laser Science APS/DLS, FiO 2020. Optica Publishing Group (formerly OSA). 2020. JM6B.18. (Optics InfoBase Conference Papers). doi: 10.1364/FIO.2020.JM6B.18

@inproceedings{da741ef6699e4571b1cdb6e6bf0221ef,

title = "Reliable oral cancer classification framework with Bayesian deep learning",

abstract = "Standard deep learning algorithms for clinical image classification are unable to understand their confidence in a decision. We developed a Bayesian deep network could estimate uncertainty to assess the reliability of oral cancer image classification.",

author = "Bofan Song and Sumsum Sunny and Shaobai Li and G. Keerthi and Sanjana Patrick and Nirza Mukhia and Shubha Gurudath and Subhashini Raghavan and Pramila Mendonca and Tsusennaro and Leivon, {Shirley T.} and Trupti Kolur and Vivek Shetty and {Vidya Bushan}, R. and Rohan Ramesh and Vijay Pillai and Alben Sigamani and Amritha Suresh and Kuriakose, {moni Abraham} and Praveen Birur and Rongguang Liang",

note = "Publisher Copyright: {\textcopyright} OSA 2020 {\textcopyright} 2020 The Author(s); 2020 Frontiers in Optics Conference, FiO 2020 ; Conference date: 14-09-2020 Through 17-09-2020",

year = "2020",

month = sep,

day = "14",

doi = "10.1364/FIO.2020.JM6B.18",

language = "English (US)",

series = "Optics InfoBase Conference Papers",

publisher = "Optica Publishing Group (formerly OSA)",

booktitle = "Frontiers in Optics - Proceedings Frontiers in Optics / Laser Science, Part of Frontiers in Optics + Laser Science APS/DLS, FiO 2020",

}

TY - GEN

T1 - Reliable oral cancer classification framework with Bayesian deep learning

AU - Song, Bofan

AU - Sunny, Sumsum

AU - Li, Shaobai

AU - Keerthi, G.

AU - Patrick, Sanjana

AU - Mukhia, Nirza

AU - Gurudath, Shubha

AU - Raghavan, Subhashini

AU - Mendonca, Pramila

AU - Tsusennaro,

AU - Leivon, Shirley T.

AU - Kolur, Trupti

AU - Shetty, Vivek

AU - Vidya Bushan, R.

AU - Ramesh, Rohan

AU - Pillai, Vijay

AU - Sigamani, Alben

AU - Suresh, Amritha

AU - Kuriakose, moni Abraham

AU - Birur, Praveen

AU - Liang, Rongguang

PY - 2020/9/14

Y1 - 2020/9/14

N2 - Standard deep learning algorithms for clinical image classification are unable to understand their confidence in a decision. We developed a Bayesian deep network could estimate uncertainty to assess the reliability of oral cancer image classification.

AB - Standard deep learning algorithms for clinical image classification are unable to understand their confidence in a decision. We developed a Bayesian deep network could estimate uncertainty to assess the reliability of oral cancer image classification.

UR - http://www.scopus.com/inward/record.url?scp=85105992262&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85105992262&partnerID=8YFLogxK

U2 - 10.1364/FIO.2020.JM6B.18

DO - 10.1364/FIO.2020.JM6B.18

M3 - Conference contribution

AN - SCOPUS:85105992262

T3 - Optics InfoBase Conference Papers

BT - Frontiers in Optics - Proceedings Frontiers in Optics / Laser Science, Part of Frontiers in Optics + Laser Science APS/DLS, FiO 2020

PB - Optica Publishing Group (formerly OSA)

T2 - 2020 Frontiers in Optics Conference, FiO 2020

Y2 - 14 September 2020 through 17 September 2020

ER -

Reliable oral cancer classification framework with Bayesian deep learning

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this