eprintid: 292
rev_number: 7
eprint_status: archive
userid: 7
dir: disk0/00/00/02/92
datestamp: 2010-05-12 17:23:36
lastmod: 2010-05-12 17:23:36
status_changed: 2010-05-12 17:23:36
type: report
metadata_visibility: show
item_issues_count: 0
creators_name: Schreuder, Jan
creators_name: van de Fliert, Barbera
creators_name: Molenaar, Jaap
corp_creators: Dr. M. Oudkerk
title: Detection of Metastases in Human Lungs from CT-Scans
ispublished: pub
subjects: medicine
studygroups: esgi33
companyname: Dr. Daniel den Hoedkliniek
full_text_status: public
abstract: One of the possibilities to assist physicians with their diagnostic work based on CT-scans would be a tool for automatic detection of metastases in human lungs. The present project stems from the ‘Dr. Daniel den Hoedkliniek’ in Rotterdam. The problem was successfully tackled during the week and resulted in a highly efficient algorithm to detect metastases from CT-data. The algorithm is restricted to metastases that are not attached to each other or to the lung edges. A first attempt to implement it into a Fortran program yielded successful results on artificial data sets. For fine-tuning of parameters the algorithm should be applied to real data from the clinic.
date: 1998
citation:   Schreuder, Jan and van de Fliert, Barbera and Molenaar, Jaap  (1998) Detection of Metastases in Human Lungs from CT-Scans.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/292/1/bolswi-cwisyl.doc