Jan Cornelis
Overview
Explore the profile of Jan Cornelis including associated specialties, affiliations and a list of published articles.
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Articles
23
Citations
168
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Recent Articles
11.
Tsinganos P, Jansen B, Cornelis J, Skodras A
Sensors (Basel)
. 2022 Mar;
22(5).
PMID: 35270841
In recent years, the successful application of Deep Learning methods to classification problems has had a huge impact in many domains. (1) Background: In biomedical engineering, the problem of gesture...
12.
Brahimetaj R, Willekens I, Massart A, Forsyth R, Cornelis J, De Mey J, et al.
BMC Cancer
. 2022 Feb;
22(1):162.
PMID: 35148703
Background: The detection of suspicious microcalcifications on mammography represents one of the earliest signs of a malignant breast tumor. Assessing microcalcifications' characteristics based on their appearance on 2D breast imaging...
13.
Papavasileiou E, Cornelis J, Jansen B
Evol Comput
. 2020 Nov;
29(1):1-73.
PMID: 33151100
NeuroEvolution (NE) refers to a family of methods for optimizing Artificial Neural Networks (ANNs) using Evolutionary Computation (EC) algorithms. NeuroEvolution of Augmenting Topologies (NEAT) is considered one of the most...
14.
Clevers E, Lutin E, Cornelis J, Van Oudenhove L
J Psychosom Res
. 2020 Sep;
138:110230.
PMID: 32927308
Objective: Gastrointestinal (GI) symptoms can be triggered by several lifestyle factors, including psychological distress, short sleep duration, and diet. It is poorly known which physiological mechanisms are involved, but the...
15.
Tsinganos P, Cornelis B, Cornelis J, Jansen B, Skodras A
Sensors (Basel)
. 2020 Sep;
20(17).
PMID: 32872508
The range of applications of electromyography-based gesture recognition has increased over the last years. A common problem regularly encountered in literature is the inadequate data availability. Data augmentation, which aims...
16.
Smets E, Velazquez E, Schiavone G, Chakroun I, DHondt E, De Raedt W, et al.
NPJ Digit Med
. 2019 Jul;
1:67.
PMID: 31304344
Physiological signals have shown to be reliable indicators of stress in laboratory studies, yet large-scale ambulatory validation is lacking. We present a large-scale cross-sectional study for ambulatory stress detection, consisting...
17.
Ji H, He J, Yang X, Deklerck R, Cornelis J
IEEE J Biomed Health Inform
. 2014 Mar;
17(3):690-8.
PMID: 24592469
In this paper, we present an autocontext model(ACM)-based automatic liver segmentation algorithm, which combines ACM, multiatlases, and mean-shift techniques to segment liver from 3-D CT images. Our algorithm is a...
18.
Tan M, Deklerck R, Cornelis J, Jansen B
Artif Intell Med
. 2013 Sep;
59(3):157-67.
PMID: 24028824
Objective: In the field of computer-aided detection (CAD) systems for lung nodules in computed tomography (CT) scans, many image features are presented and many artificial neural network (ANN) classifiers with...
19.
Tan M, Deklerck R, Jansen B, Bister M, Cornelis J
Med Phys
. 2011 Oct;
38(10):5630-45.
PMID: 21992380
Purpose: The paper presents a complete computer-aided detection (CAD) system for the detection of lung nodules in computed tomography images. A new mixed feature selection and classification methodology is applied...
20.
Munteanu A, Cernea D, Alecu A, Cornelis J, Schelkens P
IEEE Trans Vis Comput Graph
. 2010 Mar;
16(3):513-28.
PMID: 20224144
The paper investigates the novel concept of local-error control in mesh geometry encoding. In contrast to traditional mesh-coding systems that use the mean-square error as target distortion metric, this paper...