PathoVA: A visual analytics tool for pathology diagnosis and reporting

Alberto Corvò; Marc A. van Driel; Michel A. Westenberg

doi:10.1109/VAHC.2017.8387544

PathoVA: A visual analytics tool for pathology diagnosis and reporting

Alberto Corvò, Marc A. van Driel, Michel A. Westenberg

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

6 Citations (Scopus)

2 Downloads (Pure)

Abstract

We introduce PathoVA, a visual analytics system for computer aided pathology diagnosis. The diagnostic work of a pathologist involves characterizing cells and the appearance of histological sections of tissues, which are stained by techniques that highlight particular elements. Our system supports this work by recording activities in a digital tissue slide viewer, from which a diagnostic trace is constructed automatically. The visualization of the trace is enhanced with quantitative data about the tissue obtained by image analysis. Using the trace visualization, the pathologist can fill out the pathology report according to the required protocol. We demonstrate our approach on a use case of breast tissue examination. Our qualitative evaluation shows that PathoVA supports the diagnostic procedure and simplifies reporting.

Original language	English
Title of host publication	2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	77-83
Number of pages	7
ISBN (Electronic)	9781538631874
DOIs	https://doi.org/10.1109/VAHC.2017.8387544
Publication status	Published - 15 Jun 2018
Event	8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 - Phoenix, United States Duration: 1 Oct 2017 → …

Conference

Conference	8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017
Country/Territory	United States
City	Phoenix
Period	1/10/17 → …

Keywords

breast-cancer
computational pathology
computer assisted diagnosis
Digital pathology
Nottingham Score
pathology informatics
visual analytics
workflow

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/VAHC.2017.8387544

Cite this

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title = "PathoVA: A visual analytics tool for pathology diagnosis and reporting",

abstract = "We introduce PathoVA, a visual analytics system for computer aided pathology diagnosis. The diagnostic work of a pathologist involves characterizing cells and the appearance of histological sections of tissues, which are stained by techniques that highlight particular elements. Our system supports this work by recording activities in a digital tissue slide viewer, from which a diagnostic trace is constructed automatically. The visualization of the trace is enhanced with quantitative data about the tissue obtained by image analysis. Using the trace visualization, the pathologist can fill out the pathology report according to the required protocol. We demonstrate our approach on a use case of breast tissue examination. Our qualitative evaluation shows that PathoVA supports the diagnostic procedure and simplifies reporting.",

keywords = "breast-cancer, computational pathology, computer assisted diagnosis, Digital pathology, Nottingham Score, pathology informatics, visual analytics, workflow",

author = "Alberto Corv{\`o} and {van Driel}, {Marc A.} and Westenberg, {Michel A.}",

year = "2018",

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doi = "10.1109/VAHC.2017.8387544",

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booktitle = "2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017",

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}

Corvò, A, van Driel, MA & Westenberg, MA 2018, PathoVA: A visual analytics tool for pathology diagnosis and reporting. in 2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017. Institute of Electrical and Electronics Engineers, Piscataway, pp. 77-83, 8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017, Phoenix, United States, 1/10/17. https://doi.org/10.1109/VAHC.2017.8387544

PathoVA : A visual analytics tool for pathology diagnosis and reporting. / Corvò, Alberto; van Driel, Marc A.; Westenberg, Michel A.

2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017. Piscataway : Institute of Electrical and Electronics Engineers, 2018. p. 77-83.

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

TY - GEN

T1 - PathoVA

T2 - 8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017

AU - Corvò, Alberto

AU - van Driel, Marc A.

AU - Westenberg, Michel A.

PY - 2018/6/15

Y1 - 2018/6/15

N2 - We introduce PathoVA, a visual analytics system for computer aided pathology diagnosis. The diagnostic work of a pathologist involves characterizing cells and the appearance of histological sections of tissues, which are stained by techniques that highlight particular elements. Our system supports this work by recording activities in a digital tissue slide viewer, from which a diagnostic trace is constructed automatically. The visualization of the trace is enhanced with quantitative data about the tissue obtained by image analysis. Using the trace visualization, the pathologist can fill out the pathology report according to the required protocol. We demonstrate our approach on a use case of breast tissue examination. Our qualitative evaluation shows that PathoVA supports the diagnostic procedure and simplifies reporting.

AB - We introduce PathoVA, a visual analytics system for computer aided pathology diagnosis. The diagnostic work of a pathologist involves characterizing cells and the appearance of histological sections of tissues, which are stained by techniques that highlight particular elements. Our system supports this work by recording activities in a digital tissue slide viewer, from which a diagnostic trace is constructed automatically. The visualization of the trace is enhanced with quantitative data about the tissue obtained by image analysis. Using the trace visualization, the pathologist can fill out the pathology report according to the required protocol. We demonstrate our approach on a use case of breast tissue examination. Our qualitative evaluation shows that PathoVA supports the diagnostic procedure and simplifies reporting.

KW - breast-cancer

KW - computational pathology

KW - computer assisted diagnosis

KW - Digital pathology

KW - Nottingham Score

KW - pathology informatics

KW - visual analytics

KW - workflow

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U2 - 10.1109/VAHC.2017.8387544

DO - 10.1109/VAHC.2017.8387544

M3 - Conference contribution

AN - SCOPUS:85050073121

SP - 77

EP - 83

BT - 2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

Y2 - 1 October 2017

ER -

PathoVA: A visual analytics tool for pathology diagnosis and reporting

Abstract

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Keywords

UN SDGs

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