A Review of Recent Advances in Registration Techniques Applied to Minimally Invasive Therapy

Liao, Rui; Zhang, Li; Sun, Yeneng; Miao, Shun; Chefd’hotel, Christophe

doi:10.1109/tmm.2013.2244869

Cited by 58 publications

(30 citation statements)

References 143 publications

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“…The classical application of medical image registration is to align images from different modalities, e.g., pre-operative 3D CT images and intra-operative 2D X-ray projection images [141]. We can distinguish between different types of registration, depending on the dimensionality of the underlying images (2D slice, 3D volumetric, video), as reviewed in [121].…”

Section: Image Registration and Tissue Deformation Trackingmentioning

confidence: 99%

Content-based processing and analysis of endoscopic images and videos: A survey

Münzer

Schoeffmann

Böszörményi

2017

Multimed Tools Appl

109

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In recent years, digital endoscopy has established as key technology for medical screenings and minimally invasive surgery. Since then, various research communities with manifold backgrounds have picked up on the idea of processing and automatically analyzing the inherently available video signal that is produced by the endoscopic camera. Proposed works mainly include image processing techniques, pattern recognition, machine learning methods and Computer Vision algorithms. While most contributions deal with realtime assistance at procedure time, the post-procedural processing of recorded videos is still in its infancy. Many post-processing problems are based on typical Multimedia methods like indexing, retrieval, summarization and video interaction, but have only been sparsely addressed so far for this domain. The goals of this survey are (1) to introduce this research field to a broader audience in the Multimedia community to stimulate further research, (2) to describe domain-specific characteristics of endoscopic videos that need to be addressed in a pre-processing step, and (3) to systematically bring together the very diverse research results for the first time to provide a broader overview of related research that is currently not perceived as belonging together.

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Section: Image Registration and Tissue Deformation Trackingmentioning

confidence: 99%

Content-based processing and analysis of endoscopic images and videos: A survey

Münzer

Schoeffmann

Böszörményi

2017

Multimed Tools Appl

109

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“…One can cite, for example, image guided surgeries and therapies [7], biopsies [46], tracking of particular organs [12] and minimally-invasive procedures [28,17]. In such a context, slice-to-volume registration is a key element for bringing high resolution annotated data into the operating room.…”

Section: Motivationmentioning

confidence: 99%

Graph-Based Slice-to-Volume Deformable Registration

Ferrante

Paragios

2017

Int J Comput Vis

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Deformable image registration is a fundamental problem in computer vision and medical image computing. In this paper we investigate the use of graphical models in the context of a particular type of image registration problem, known as slice-to-volume registration. We introduce a scalable, modular and flexible formulation that can accommodate low-rank and high order terms, that simultaneously selects the plane and estimates the in-plane deformation through a single shot optimization approach. The proposed framework is instantiated into different variants seeking either a compromise between computational efficiency (soft plane selection constraints and approximate definition of the data similarity terms through pair-wise components) or exact definition of the data terms and the constraints on the plane selection. Simulated and real-data in the context of ultrasound and magnetic resonance registration (where both framework instantiations as well as different optimization strategies are considered) demonstrate the potentials of our method.

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“…It has also been shown that the number of attempts required to sample a clinically significant tumor increases as needle delivery error of a biopsy system increases . Among other techniques, 3D to 2D registration is invaluable to reduce needle delivery error and has been investigated in a broad spectrum of interventions . Therefore, to compensate for misalignment error caused by prostate motion, two correction methods are feasible: (a) performing a single, intermittent user initiated registration correction before firing the biopsy needle, and (b) automatic, continuous correcting for any prostate motion throughout the biopsy procedure.…”

Section: Introductionmentioning

confidence: 99%

Real‐time registration of 3D to 2D ultrasound images for image‐guided prostate biopsy

et al. 2017

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The presented method encourages real-time implementation of motion compensation algorithms in prostate biopsy with clinically acceptable registration errors. Continuous motion compensation demonstrated registration accuracy with submillimeter and subdegree error, while performing < 50 ms computation times. Image registration technique approaching the frame rate of an ultrasound system offers a key advantage to be smoothly integrated to the clinical workflow. In addition, this technique could be used further for a variety of image-guided interventional procedures to treat and diagnose patients by improving targeting accuracy.

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A Review of Recent Advances in Registration Techniques Applied to Minimally Invasive Therapy

Cited by 58 publications

References 143 publications

Content-based processing and analysis of endoscopic images and videos: A survey

Content-based processing and analysis of endoscopic images and videos: A survey

Graph-Based Slice-to-Volume Deformable Registration

Real‐time registration of 3D to 2D ultrasound images for image‐guided prostate biopsy

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