Towards to deep neural network application with limited training data: Synthesis of melanoma's diffuse reflectance spectral images

Katrina Bolochko; Dmitrijs Bliznuks; Dilshat Uteshev; Ilze Lihacova; Alexey Lihachev; Yuriy Chizhov; Andrey Bondarenko

doi:10.1117/12.2527173

Towards to deep neural network application with limited training data: Synthesis of melanoma's diffuse reflectance spectral images

Katrina Bolochko^*
, Dmitrijs Bliznuks
, Dilshat Uteshev
, Ilze Lihacova
, Alexey Lihachev
, Yuriy Chizhov
, Andrey Bondarenko

^*Šī darba korespondējošais autors

Atomfizikas un spektroskopijas institūts

Rīgas Tehniskā universitāte
C.T.Co. LTD

Zinātniskās darbības rezultāts: Nodaļa grāmatā/enciklopēdijā/konferences krājumā › Konferences zinātniskais raksts › Pētniecība › koleģiāli recenzēts

1 Atsauce (Scopus)

Kopsavilkums

The goal of our study is to train artificial neural networks (ANN) using multispectral images of melanoma. Since the number of multispectral images of melanomas is limited, we offer to synthesize them from multispectral images of benign skin lesions. We used the previously created melanoma diagnostic criterion p'. This criterion is calculated from multispectral images of skin lesions captured under 526nm, 663nm, and 964nm LED illumination. We synthesize these three images from multispectral images of nevus so that the p' map matches the melanoma criteria (the values in the lesion area is >1, respectively). Demonstrated results show that by transforming multispectral images of benign nevus is possible to get a reliable multispectral images of melanoma usable for ANN training.

Oriģinālvaloda	Angļu
Publikācijas avota nosaukums	Diffuse Optical Spectroscopy and Imaging VII
Redaktori	Hamid Dehghani, Heidrun Wabnitz
Izdevējs	SPIE
ISBN (Elektroniski)	9781510628410
DOIs	https://doi.org/10.1117/12.2527173
Publikācijas statuss	Publicēts - 2019
Pasākums	Diffuse Optical Spectroscopy and Imaging VII 2019 - Munich, Vācija Ilgums: 23 jūn. 2019 → 25 jūn. 2019

Publikāciju sērijas

Nosaukums	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Sējums	11074
ISSN (Drukātā versija)	1605-7422

Konference

Konference	Diffuse Optical Spectroscopy and Imaging VII 2019
Valsts/Teritorija	Vācija
Pilsēta	Munich
Periods	23/06/19 → 25/06/19

ANO IAM

Šis izpildes rezultāts palīdz sasniegt šādus ANO ilgtspējīgas attīstības mērķus (IAM)

3. IAM — Laba Veselība un Labbūtība

Piekļuve Dokumentiem

10.1117/12.2527173

Citi faili un saites

Saite uz publikāciju Scopus

Citēt šo

Bolochko, K., Bliznuks, D., Uteshev, D., Lihacova, I., Lihachev, A., Chizhov, Y., & Bondarenko, A. (2019). Towards to deep neural network application with limited training data: Synthesis of melanoma's diffuse reflectance spectral images. (gadā) H. Dehghani, & H. Wabnitz (Red.), Diffuse Optical Spectroscopy and Imaging VII Zinātniskais raksts 110741O (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Sēj. 11074). SPIE. https://doi.org/10.1117/12.2527173

@inproceedings{732e64880513430cb0ef49a0b1408922,

title = "Towards to deep neural network application with limited training data: Synthesis of melanoma's diffuse reflectance spectral images",

abstract = "The goal of our study is to train artificial neural networks (ANN) using multispectral images of melanoma. Since the number of multispectral images of melanomas is limited, we offer to synthesize them from multispectral images of benign skin lesions. We used the previously created melanoma diagnostic criterion p'. This criterion is calculated from multispectral images of skin lesions captured under 526nm, 663nm, and 964nm LED illumination. We synthesize these three images from multispectral images of nevus so that the p' map matches the melanoma criteria (the values in the lesion area is >1, respectively). Demonstrated results show that by transforming multispectral images of benign nevus is possible to get a reliable multispectral images of melanoma usable for ANN training.",

keywords = "artificial neural networks, diffuse reflectance, early diagnostics, skin cancer",

author = "Katrina Bolochko and Dmitrijs Bliznuks and Dilshat Uteshev and Ilze Lihacova and Alexey Lihachev and Yuriy Chizhov and Andrey Bondarenko",

note = "Publisher Copyright: {\textcopyright} 2019 SPIE.; Diffuse Optical Spectroscopy and Imaging VII 2019 ; Conference date: 23-06-2019 Through 25-06-2019",

year = "2019",

doi = "10.1117/12.2527173",

language = "English",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

publisher = "SPIE",

editor = "Hamid Dehghani and Heidrun Wabnitz",

booktitle = "Diffuse Optical Spectroscopy and Imaging VII",

address = "United States",

}

Bolochko, K, Bliznuks, D, Uteshev, D, Lihacova, I, Lihachev, A, Chizhov, Y & Bondarenko, A 2019, Towards to deep neural network application with limited training data: Synthesis of melanoma's diffuse reflectance spectral images. (kur) H Dehghani & H Wabnitz (red.), Diffuse Optical Spectroscopy and Imaging VII., 110741O, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, sēj. 11074, SPIE, Diffuse Optical Spectroscopy and Imaging VII 2019, Munich, Vācija, 23/06/19. https://doi.org/10.1117/12.2527173

Towards to deep neural network application with limited training data: Synthesis of melanoma's diffuse reflectance spectral images. / Bolochko, Katrina; Bliznuks, Dmitrijs; Uteshev, Dilshat u.c.
Diffuse Optical Spectroscopy and Imaging VII. red. / Hamid Dehghani; Heidrun Wabnitz. SPIE, 2019. 110741O (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Sēj. 11074).

Zinātniskās darbības rezultāts: Nodaļa grāmatā/enciklopēdijā/konferences krājumā › Konferences zinātniskais raksts › Pētniecība › koleģiāli recenzēts

TY - GEN

T1 - Towards to deep neural network application with limited training data

T2 - Diffuse Optical Spectroscopy and Imaging VII 2019

AU - Bolochko, Katrina

AU - Bliznuks, Dmitrijs

AU - Uteshev, Dilshat

AU - Lihacova, Ilze

AU - Lihachev, Alexey

AU - Chizhov, Yuriy

AU - Bondarenko, Andrey

PY - 2019

Y1 - 2019

N2 - The goal of our study is to train artificial neural networks (ANN) using multispectral images of melanoma. Since the number of multispectral images of melanomas is limited, we offer to synthesize them from multispectral images of benign skin lesions. We used the previously created melanoma diagnostic criterion p'. This criterion is calculated from multispectral images of skin lesions captured under 526nm, 663nm, and 964nm LED illumination. We synthesize these three images from multispectral images of nevus so that the p' map matches the melanoma criteria (the values in the lesion area is >1, respectively). Demonstrated results show that by transforming multispectral images of benign nevus is possible to get a reliable multispectral images of melanoma usable for ANN training.

AB - The goal of our study is to train artificial neural networks (ANN) using multispectral images of melanoma. Since the number of multispectral images of melanomas is limited, we offer to synthesize them from multispectral images of benign skin lesions. We used the previously created melanoma diagnostic criterion p'. This criterion is calculated from multispectral images of skin lesions captured under 526nm, 663nm, and 964nm LED illumination. We synthesize these three images from multispectral images of nevus so that the p' map matches the melanoma criteria (the values in the lesion area is >1, respectively). Demonstrated results show that by transforming multispectral images of benign nevus is possible to get a reliable multispectral images of melanoma usable for ANN training.

KW - artificial neural networks

KW - diffuse reflectance

KW - early diagnostics

KW - skin cancer

UR - https://www.scopus.com/pages/publications/85076892143

U2 - 10.1117/12.2527173

DO - 10.1117/12.2527173

M3 - Conference paper

AN - SCOPUS:85076892143

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Diffuse Optical Spectroscopy and Imaging VII

A2 - Dehghani, Hamid

A2 - Wabnitz, Heidrun

PB - SPIE

Y2 - 23 June 2019 through 25 June 2019

ER -

Bolochko K, Bliznuks D, Uteshev D, Lihacova I, Lihachev A, Chizhov Y u.c. Towards to deep neural network application with limited training data: Synthesis of melanoma's diffuse reflectance spectral images. (gadā) Dehghani H, Wabnitz H, redaktori, Diffuse Optical Spectroscopy and Imaging VII. SPIE. 2019. 110741O. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). doi: 10.1117/12.2527173

Towards to deep neural network application with limited training data: Synthesis of melanoma's diffuse reflectance spectral images

Kopsavilkums

Publikāciju sērijas

Konference

ANO IAM

Piekļuve Dokumentiem

Citi faili un saites

Nospiedums

Citēt šo