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 | |
| 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 | United States |
| City | Phoenix |
| Period | 1/10/17 → … |
Fingerprint
Keywords
- breast-cancer
- computational pathology
- computer assisted diagnosis
- Digital pathology
- Nottingham Score
- pathology informatics
- visual analytics
- workflow
Cite this
}
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 - A visual analytics tool for pathology diagnosis and reporting
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
UR - http://www.scopus.com/inward/record.url?scp=85050073121&partnerID=8YFLogxK
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
ER -