Gabor filter based localization of needles in ultrasound guided robotic interventions

Name: Gabor filter based localization of needles in ultrasound guided robotic interventions
Author: Kaya, Mert, Bebek, Özkan

İsim	Gabor filter based localization of needles in ultrasound guided robotic interventions
Yazar	Kaya, Mert, Bebek, Özkan
Basım Tarihi:	2014
Basım Yeri	- IEEE
Konu	Gabor filters, Control engineering computing, Entropy, Image enhancement, Image segmentation, Medical image processing, Medical robotics, Probability, Robot vision, Ultrasonic imaging
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	1558-2809
Kayıt Numarası	29f0599f-6465-4d1a-ab8b-fea87cb6a496
Lokasyon	Mechanical Engineering
Tarih	2014
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	This paper presents an entropy based parameter tuning method for needle segmentation, and a probability map based needle tip estimation method using Gabor-based line filter. The proposed automatic parameter tuning method optimizes the threshold value that is used by the Otsu's thresholding technique to binarize the ultrasound image. A probability map is created to estimate the needle tip location using the Gabor filtered image and the binarized image. The pixel with the maximum probability represents the needle tip location. Finally, an enhancement method to improve needle visibility is proposed. The proposed methods are experimentally tested in four different phantoms and distilled water. The image processing time is reduced by 24% using the proposed tuning method, and the needle tip location can be successfully estimated using the probability map.
DOI	10.1109/IST.2014.6958456

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Gabor filter based localization of needles in ultrasound guided robotic interventions

Yazar Kaya, Mert, Bebek, Özkan

Basım Tarihi 2014

Basım Yeri - IEEE

Konu Gabor filters, Control engineering computing, Entropy, Image enhancement, Image segmentation, Medical image processing, Medical robotics, Probability, Robot vision, Ultrasonic imaging

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 1558-2809

Kayıt Numarası 29f0599f-6465-4d1a-ab8b-fea87cb6a496

Lokasyon Mechanical Engineering

Tarih 2014

Notlar Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Örnek Metin This paper presents an entropy based parameter tuning method for needle segmentation, and a probability map based needle tip estimation method using Gabor-based line filter. The proposed automatic parameter tuning method optimizes the threshold value that is used by the Otsu's thresholding technique to binarize the ultrasound image. A probability map is created to estimate the needle tip location using the Gabor filtered image and the binarized image. The pixel with the maximum probability represents the needle tip location. Finally, an enhancement method to improve needle visibility is proposed. The proposed methods are experimentally tested in four different phantoms and distilled water. The image processing time is reduced by 24% using the proposed tuning method, and the needle tip location can be successfully estimated using the probability map.

DOI 10.1109/IST.2014.6958456