Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions

Alessio Gallucci; Dmitry Znamenskiy; Nicola Pezzotti; Milan Petkovic

doi:10.1007/978-3-030-68763-2_31

Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions

Alessio Gallucci (Corresponding author)
, Dmitry Znamenskiy
, Nicola Pezzotti
, Milan Petkovic

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

13 Downloads (Pure)

Abstract

Recent work on the classification of microscopic skin lesions does not consider how the presence of skin hair may affect diagnosis. In this work, we investigate how deep-learning models can handle a varying amount of skin hair during their predictions. We present an automated processing pipeline that tests the performance of the classification model. We conclude that, under realistic conditions, modern day classification models are robust to the presence of skin hair and we investigate three architectural choices (Resnet50, InceptionV3, Densenet121) that make them so.

Original language	English
Title of host publication	Pattern Recognition. ICPR International Workshops and Challenges
Subtitle of host publication	Virtual Event, January 10–15, 2021, Proceedings
Editors	Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani
Place of Publication	Cham
Publisher	Springer
Pages	406-416
Number of pages	11
ISBN (Electronic)	978-3-030-68763-2
ISBN (Print)	978-3-030-68762-5
DOIs	https://doi.org/10.1007/978-3-030-68763-2_31
Publication status	Published - 21 Feb 2021
Event	25th International Conference on Pattern Recognition Workshops, ICPR 2020 - Milan, Italy Duration: 10 Jan 2021 → 15 Jan 2021 Conference number: 25 https://www.micc.unifi.it/icpr2020/

Publication series

Name	Lecture Notes in Computer Science (LNCS)
Volume	12661
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Volume	12661
ISSN (Print)	3004-9946
ISSN (Electronic)	3004-9954

Conference

Conference	25th International Conference on Pattern Recognition Workshops, ICPR 2020
Abbreviated title	ICPR 2020
Country/Territory	Italy
City	Milan
Period	10/01/21 → 15/01/21
Internet address	https://www.micc.unifi.it/icpr2020/

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

Augmentations
Deep learning
Dermatology
Hair detection
Imaging
Melanoma
Skin lesion

Access to Document

10.1007/978-3-030-68763-2_31

pdfFinal published version, 2.1 MBLicence: TAVERNE

Cite this

Gallucci, A., Znamenskiy, D., Pezzotti, N., & Petkovic, M. (2021). Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions. In A. Del Bimbo, R. Cucchiara, S. Sclaroff, G. M. Farinella, T. Mei, M. Bertini, H. J. Escalante, & R. Vezzani (Eds.), Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings (pp. 406-416). (Lecture Notes in Computer Science (LNCS); Vol. 12661), (Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP); Vol. 12661). Springer. https://doi.org/10.1007/978-3-030-68763-2_31

Gallucci, Alessio ; Znamenskiy, Dmitry ; Pezzotti, Nicola et al. / Don’t Tear Your Hair Out : Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions. Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings. editor / Alberto Del Bimbo ; Rita Cucchiara ; Stan Sclaroff ; Giovanni Maria Farinella ; Tao Mei ; Marco Bertini ; Hugo Jair Escalante ; Roberto Vezzani. Cham : Springer, 2021. pp. 406-416 (Lecture Notes in Computer Science (LNCS)). (Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)).

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title = "Don{\textquoteright}t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions",

abstract = "Recent work on the classification of microscopic skin lesions does not consider how the presence of skin hair may affect diagnosis. In this work, we investigate how deep-learning models can handle a varying amount of skin hair during their predictions. We present an automated processing pipeline that tests the performance of the classification model. We conclude that, under realistic conditions, modern day classification models are robust to the presence of skin hair and we investigate three architectural choices (Resnet50, InceptionV3, Densenet121) that make them so.",

keywords = "Augmentations, Deep learning, Dermatology, Hair detection, Imaging, Melanoma, Skin lesion",

author = "Alessio Gallucci and Dmitry Znamenskiy and Nicola Pezzotti and Milan Petkovic",

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Gallucci, A, Znamenskiy, D, Pezzotti, N & Petkovic, M 2021, Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions. in A Del Bimbo, R Cucchiara, S Sclaroff, GM Farinella, T Mei, M Bertini, HJ Escalante & R Vezzani (eds), Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings. Lecture Notes in Computer Science (LNCS), vol. 12661, Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP), vol. 12661, Springer, Cham, pp. 406-416, 25th International Conference on Pattern Recognition Workshops, ICPR 2020, Milan, Italy, 10/01/21. https://doi.org/10.1007/978-3-030-68763-2_31

Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions. / Gallucci, Alessio (Corresponding author); Znamenskiy, Dmitry; Pezzotti, Nicola et al.
Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings. ed. / Alberto Del Bimbo; Rita Cucchiara; Stan Sclaroff; Giovanni Maria Farinella; Tao Mei; Marco Bertini; Hugo Jair Escalante; Roberto Vezzani. Cham: Springer, 2021. p. 406-416 (Lecture Notes in Computer Science (LNCS); Vol. 12661), (Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP); Vol. 12661).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Don’t Tear Your Hair Out

T2 - 25th International Conference on Pattern Recognition Workshops, ICPR 2020

AU - Gallucci, Alessio

AU - Znamenskiy, Dmitry

AU - Pezzotti, Nicola

AU - Petkovic, Milan

N1 - Conference code: 25

PY - 2021/2/21

Y1 - 2021/2/21

N2 - Recent work on the classification of microscopic skin lesions does not consider how the presence of skin hair may affect diagnosis. In this work, we investigate how deep-learning models can handle a varying amount of skin hair during their predictions. We present an automated processing pipeline that tests the performance of the classification model. We conclude that, under realistic conditions, modern day classification models are robust to the presence of skin hair and we investigate three architectural choices (Resnet50, InceptionV3, Densenet121) that make them so.

AB - Recent work on the classification of microscopic skin lesions does not consider how the presence of skin hair may affect diagnosis. In this work, we investigate how deep-learning models can handle a varying amount of skin hair during their predictions. We present an automated processing pipeline that tests the performance of the classification model. We conclude that, under realistic conditions, modern day classification models are robust to the presence of skin hair and we investigate three architectural choices (Resnet50, InceptionV3, Densenet121) that make them so.

KW - Augmentations

KW - Deep learning

KW - Dermatology

KW - Hair detection

KW - Imaging

KW - Melanoma

KW - Skin lesion

UR - https://www.scopus.com/pages/publications/85104325768

U2 - 10.1007/978-3-030-68763-2_31

DO - 10.1007/978-3-030-68763-2_31

M3 - Conference contribution

AN - SCOPUS:85104325768

SN - 978-3-030-68762-5

T3 - Lecture Notes in Computer Science (LNCS)

SP - 406

EP - 416

BT - Pattern Recognition. ICPR International Workshops and Challenges

A2 - Del Bimbo, Alberto

A2 - Cucchiara, Rita

A2 - Sclaroff, Stan

A2 - Farinella, Giovanni Maria

A2 - Mei, Tao

A2 - Bertini, Marco

A2 - Escalante, Hugo Jair

A2 - Vezzani, Roberto

PB - Springer

CY - Cham

Y2 - 10 January 2021 through 15 January 2021

ER -

Gallucci A, Znamenskiy D, Pezzotti N, Petkovic M. Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions. In Del Bimbo A, Cucchiara R, Sclaroff S, Farinella GM, Mei T, Bertini M, Escalante HJ, Vezzani R, editors, Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings. Cham: Springer. 2021. p. 406-416. (Lecture Notes in Computer Science (LNCS)). (Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)). doi: 10.1007/978-3-030-68763-2_31

Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Data set of multi-source dermatoscopic images of skin hair for skin lesions

Cite this

Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Datasets

Data set of multi-source dermatoscopic images of skin hair for skin lesions

Cite this