P3227 Improved automated stent border detection in intravascular ultrasound pullback series

2003 ◽  
Vol 24 (5) ◽  
pp. 606
Author(s):  
J DIJKSTRA
1996 ◽  
Vol 27 (2) ◽  
pp. 240
Author(s):  
Stephen P. Wiet ◽  
Stuart A. Greenfield ◽  
Reena Sinha ◽  
Gorav Ailawadi ◽  
Michael J. Vonesh ◽  
...  

2021 ◽  
Vol 10 (1) ◽  
pp. 508-515
Author(s):  
Suhaili Beeran Kutty ◽  
Rahmita Wirza O. K. Rahmat ◽  
Sazzli Shahlan Kassim ◽  
Hizmawati Madzin ◽  
Hazlina Hamdan

In diagnosing coronary artery disease, measurement of the cross-sectional area of the lumen, maximum and minimum diameter is very important. Mainly, it will be used to confirm the diagnosing, to predict the stenosis if any and to ensure the size of the stent to be used. However, the measurement only offers by the existing software and some of the software needs human interaction to complete the process. The purpose of this paper is to present the algorithm to measure the region of interest (ROI) on intravascular ultrasound (IVUS) using an image processing technique. The methodology starts with image acquisition process followed by image segmentation. After that, border detection for each ROI was detected and the algorithm was applied to calculate the corresponding region. The result shows that the measurement is accurate and could be used not only for IVUS but applicable to solid circle and unsymmetrical circle shape. 


Author(s):  
Jouke Dijkstra ◽  
Gerhard Koning ◽  
Joan C. Tuinenburg ◽  
Pranobe V. Oemrawsingh ◽  
Clemens von Birgelen ◽  
...  

2001 ◽  
Vol 1230 ◽  
pp. 916-922 ◽  
Author(s):  
Jouke Dijkstra ◽  
Gerhard Koning ◽  
Joan C. Tuinenburg ◽  
Pranobe V. Oemrawsingh ◽  
Clemens von Birgelen ◽  
...  

2005 ◽  
Vol 78 (926) ◽  
pp. 122-129 ◽  
Author(s):  
C V Bourantas ◽  
M E Plissiti ◽  
D I Fotiadis ◽  
V C Protopappas ◽  
G V Mpozios ◽  
...  

2002 ◽  
Vol 39 ◽  
pp. 451 ◽  
Author(s):  
Jouke Dijkstra ◽  
Gerhard Koning ◽  
Joan C. Tuinenburg ◽  
Pranobe V. Oemrawsingh ◽  
Johan H.C. Reiber

Author(s):  
Zahra Rezaei ◽  
Ali Selamat ◽  
Arash Taki ◽  
Mohd Shafry Mohd Rahim ◽  
Mohammed Rafiq Abdul Kadir ◽  
...  

Virtual Histology- Intravascular Ultrasound (VH-IVUS) image is an available method for visualizing plaque component to detect thin cap fibroatheroma. Nevertheless, this imaging modality has considerable limitations to extract the plaque component features and identifying the TCFA plaque. The aim of this paper is to improve the identification of TCFA using fusion of IVUS and VH-IVUS images. In order to generate the automatic technique for reducing the human interaction, a new method namely Active Contour based Plaque Border Detection (ACPB) is proposed. In order to perform the pixel wise classification, hybrid of K-means algorithm with Particle Swarm Optimization and Plaque based Minimum Euclidean Distance (KMPSO-PMED) method is presented to classify the plaque region as well. Moreover, to obtain more significant information of imaging modalities, fusion of two different images consisting of VH-IVUS and IVUS is performed. Therefore, geometric features are extracted from the plaque region and combine with IVUS features. Furthermore, different group of plaque features are divided by means of the histopathological studies. SVM classifiers is applied to detect the TCFA and non-TCFA plaques. The proposed method is applied on 566 in-vivo IVUS and their matching VH-IVUS images obtained from 9 patients. The best result of SVM illustrates the accuracy rates of 99.41% for classification of TCFA plaque. The results prove that the highest accuracy is achieved by integrated features of IVUS and VH-IVUS images.


2003 ◽  
Vol 1256 ◽  
pp. 1111-1116 ◽  
Author(s):  
Jouke Dijkstra ◽  
Gerhard Koning ◽  
Joan C Tuinenburg ◽  
Pranobe V Oemrawsingh ◽  
Johan H.C Reiber

2012 ◽  
Vol 16 (6) ◽  
pp. 1085-1100 ◽  
Author(s):  
Francesco Ciompi ◽  
Oriol Pujol ◽  
Carlo Gatta ◽  
Marina Alberti ◽  
Simone Balocco ◽  
...  

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