An Automated System for the Detection and Diagnosis of Kidney Lesions in Children from Scintigraphy Images
(2011) 17th Scandinavian Conference on Image Analysis (SCIA 2011) 6688. p.489-500- Abstract
- Designing a system for computer aided diagnosis is a complex procedure requiring an understanding of the biology of the disease, insight into hospital workflow and awareness of available technical solutions. This paper aims to show that a valuable system can be designed for diagnosing kidney lesions in children and adolescents from 99m Tc-DMSA scintigraphy images. We present the chain of analysis and provide a discussion of its performance. On a per-lesion basis, the classification reached an ROC-curve area of 0.96 (sensitivity/specificity e.g. 97%/85%) measured using an independent test group consisting of 56 patients with 730 candidate lesions. We conclude that the presented system for diagnostic support has the potential of increasing... (More)
- Designing a system for computer aided diagnosis is a complex procedure requiring an understanding of the biology of the disease, insight into hospital workflow and awareness of available technical solutions. This paper aims to show that a valuable system can be designed for diagnosing kidney lesions in children and adolescents from 99m Tc-DMSA scintigraphy images. We present the chain of analysis and provide a discussion of its performance. On a per-lesion basis, the classification reached an ROC-curve area of 0.96 (sensitivity/specificity e.g. 97%/85%) measured using an independent test group consisting of 56 patients with 730 candidate lesions. We conclude that the presented system for diagnostic support has the potential of increasing the quality of care regarding this type of examination. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2214442
- author
- Landgren, Matilda LU ; Sjöstrand, Karl ; Ohlsson, Mattias LU ; Ståhl, Daniel LU ; Overgaard, Niels Christian LU ; Åström, Karl LU ; Sixt, Rune and Edenbrandt, Lars LU
- organization
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Computer Aided Diagnosis – Nuclear Imaging – Active Shape Models – Artificial Neural Networks
- host publication
- Lecture Notes in Computer Science
- editor
- Heyden, Anders and Kahl, Fredrik
- volume
- 6688
- pages
- 12 pages
- publisher
- Springer
- conference name
- 17th Scandinavian Conference on Image Analysis (SCIA 2011)
- conference location
- Ystad, Sweden
- conference dates
- 2011-05-23 - 2011-05-27
- external identifiers
-
- wos:000308543900046
- scopus:79957506173
- ISSN
- 0302-9743
- 1611-3349
- ISBN
- 978-3-642-21227-7 (online)
- 978-3-642-21226-0 (print)
- DOI
- 10.1007/978-3-642-21227-7_46
- language
- English
- LU publication?
- yes
- id
- e0d96be1-b612-4300-853d-4b813387f7d7 (old id 2214442)
- date added to LUP
- 2016-04-01 11:04:56
- date last changed
- 2024-08-12 12:53:00
@inproceedings{e0d96be1-b612-4300-853d-4b813387f7d7, abstract = {{Designing a system for computer aided diagnosis is a complex procedure requiring an understanding of the biology of the disease, insight into hospital workflow and awareness of available technical solutions. This paper aims to show that a valuable system can be designed for diagnosing kidney lesions in children and adolescents from 99m Tc-DMSA scintigraphy images. We present the chain of analysis and provide a discussion of its performance. On a per-lesion basis, the classification reached an ROC-curve area of 0.96 (sensitivity/specificity e.g. 97%/85%) measured using an independent test group consisting of 56 patients with 730 candidate lesions. We conclude that the presented system for diagnostic support has the potential of increasing the quality of care regarding this type of examination.}}, author = {{Landgren, Matilda and Sjöstrand, Karl and Ohlsson, Mattias and Ståhl, Daniel and Overgaard, Niels Christian and Åström, Karl and Sixt, Rune and Edenbrandt, Lars}}, booktitle = {{Lecture Notes in Computer Science}}, editor = {{Heyden, Anders and Kahl, Fredrik}}, isbn = {{978-3-642-21227-7 (online)}}, issn = {{0302-9743}}, keywords = {{Computer Aided Diagnosis – Nuclear Imaging – Active Shape Models – Artificial Neural Networks}}, language = {{eng}}, pages = {{489--500}}, publisher = {{Springer}}, title = {{An Automated System for the Detection and Diagnosis of Kidney Lesions in Children from Scintigraphy Images}}, url = {{http://dx.doi.org/10.1007/978-3-642-21227-7_46}}, doi = {{10.1007/978-3-642-21227-7_46}}, volume = {{6688}}, year = {{2011}}, }