User profiles for Dirk Smeets

Dirk Smeets

icometrix, Vrije Universiteit Brussel (VUB)
Verified email at icometrix.com
Cited by 6783

Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge

…, J Ehrhardt, R Werner, D Smeets… - IEEE transactions on …, 2011 - ieeexplore.ieee.org
<?Pub Dtl=""?> EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010)
is a public platform for fair and meaningful comparison of registration algorithms which are …

Longitudinal multiple sclerosis lesion segmentation: resource and challenge

…, LO Iheme, D Unay, S Jain, DM Sima, D Smeets… - NeuroImage, 2017 - Elsevier
In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation
challenge providing training and test data to registered participants. The training data …

[HTML][HTML] Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images

…, F Maes, S Van Huffel, H Vrenken, D Smeets - NeuroImage: Clinical, 2015 - Elsevier
The location and extent of white matter lesions on magnetic resonance imaging (MRI) are
important criteria for diagnosis, follow-up and prognosis of multiple sclerosis (MS). Clinical …

A comparison of methods for non-rigid 3D shape retrieval

…, Y Ohishi, F Porikli, M Reuter, I Sipiran, D Smeets… - Pattern Recognition, 2013 - Elsevier
Non-rigid 3D shape retrieval has become an active and important research topic in content-based
3D object retrieval. The aim of this paper is to measure and compare the performance …

SHREC 2011: robust feature detection and description benchmark

…, R Litman, J Reininghaus, I Sipiran, D Smeets… - arXiv preprint arXiv …, 2011 - arxiv.org
Feature-based approaches have recently become very popular in computer vision and image
analysis applications, and are becoming a promising direction in shape retrieval. SHREC'…

[PDF][PDF] SHREC'10 Track: Non-rigid 3D Shape Retrieval.

…, J Hermans, R Ohbuchi, C Shu, D Smeets… - 3DOR …, 2010 - icmc.usp.br
Non-rigid 3D shape retrieval has become a research hotpot in communities of computer
graphics, computer vision, pattern recognition, etc. In this paper, we present the results of the …

meshSIFT: Local surface features for 3D face recognition under expression variations and partial data

D Smeets, J Keustermans, D Vandermeulen… - Computer Vision and …, 2013 - Elsevier
Matching 3D faces for recognition is a challenging task caused by the presence of expression
variations, missing data, and outliers. In this paper the meshSIFT algorithm and its use for …

Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification

D Smeets, D Loeckx, B Stijnen, B De Dobbelaer… - Medical image …, 2010 - Elsevier
In this paper, a specific method is presented to facilitate the semi-automatic segmentation of
liver tumors and liver metastases in CT images. Accurate and reliable segmentation of …

Feature detection on 3D face surfaces for pose normalisation and recognition

…, T Fabry, J Keustermans, D Smeets… - 2010 Fourth IEEE …, 2010 - ieeexplore.ieee.org
This paper presents a SIFT algorithm adapted for 3D surfaces (called meshSIFT) and its
applications to 3D face pose normalisation and recognition. The algorithm allows reliable …

Objective 3D face recognition: Evolution, approaches and challenges

D Smeets, P Claes, D Vandermeulen… - Forensic science …, 2010 - Elsevier
Face recognition is a natural human ability and a widely accepted identification and authentication
method. In modern legal settings, a lot of credence is placed on identifications made …