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Output details

15 - General Engineering

Brunel University London

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Output 42 of 258 in the submission
Article title

ATD: a multi-platform for semi-automatic 3D detection of kidneys and their pathology in real-time

Type
D - Journal article
Title of journal
IEEE Transactions on Human-Machine Systems
Article number
-
Volume number
N/A
Issue number
-
First page of article
N/A
ISSN of journal
2168-2291
Year of publication
2013
URL
-
Number of additional authors
5
Additional information

This research outlines an integrated system combining two distinct platforms: the first uses “DoctorEye” to accurately identify kidneys in an abdominal set of MRIs; the second focuses on their pathology, identifying any abnormalities found and providing real metrics on tumours and cysts that can later be used to simulate the effect of cancer therapy. The system makes use of “Templates” that clinicians originally create to accurately detect organs and custom-made image processing algorithms capable of swiftly identifying renal pathologies. The system was tested in over 500 MRI images and yields an average accuracy of 97.2%, outperforming all existing systems.

Interdisciplinary
-
Cross-referral requested
-
Research group
None
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-