Optimizing boundary detection via Simulated Search with applications to multi-modal heart segmentation

Peters, Jörg; Ecabert, Olivier; Meyer, Carsten; Kneser, Reinhard; Weese, Jürgen

doi:10.1016/j.media.2009.10.004

Cited by 91 publications

(89 citation statements)

References 50 publications

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“…Of course, as a first major ingredient, this requires the construction of accurate anatomical models which suitably represent the actual geometrical attributes of the patient considered, usually based on medical imaging data [38]. The next -at least equally important, and most challenging -stage consists in "personalizing" the biophysical characteristics of a cardiac model in order to reproduce the specificities of the patient, as e.g.…”

Section: Introductionmentioning

confidence: 99%

Estimation of tissue contractility from cardiac cine-MRI using a biomechanical heart model

Chabiniok

Moireau

Lesault

et al. 2011

Biomech Model Mechanobiol

129

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Section: Introductionmentioning

confidence: 99%

Estimation of tissue contractility from cardiac cine-MRI using a biomechanical heart model

Chabiniok

Moireau

Lesault

et al. 2011

Biomech Model Mechanobiol

129

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“…From the difference image between the 2 UTE images, a number of regions of interest were segmented (soft tissue, cortical bones, liver and lungs) and used to construct the anatomical phantom. The myocardium, heart ventricles and large vessels were also segmented using a different ECG triggered balanced B-TFE MRI scan during free breathing (TR/TE 4.7 ms/2.36 ms, TFE factor 26, o ) [15,31]. The scan was subsequently respiratory gated again to the end-exhale position using a virtual navigator.…”

Section: D Anatomical Phantommentioning

confidence: 99%

A 5D computational phantom for pharmacokinetic simulation studies in dynamic emission tomography

Kotasidis

Tsoumpas

Polycarpou

et al. 2014

Computerized Medical Imaging and Graphics

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Introduction: Dynamic image acquisition protocols are increasingly used in emission tomography for drug development and clinical research. As such, there is a need for computational phantoms to accurately describe both the spatial and temporal distribution of radiotracers, also accounting for periodic and non-periodic physiological processes occurring during data acquisition. Methods:A new 5D anthropomorphic digital phantom was developed based on a generic simulation platform, for accurate parametric imaging simulation studies in emission tomography. The phantom is based on high spatial and temporal information derived from real 4D MR data and a detailed multi-compartmental pharmacokinetic modelling simulator. Results:The proposed phantom is comprised of 3 spatial and 2 temporal dimensions, including periodic physiological processes due to respiratory motion and non-periodic functional processes due to tracer kinetics. Conclusions:The envisaged applications of this digital phantom include the development and evaluation of motion correction and 4D image reconstruction algorithms in PET and SPECT, development of protocols and methods for tracer and drug development as well as new pharmacokinetic parameter estimation algorithms, amongst others. Although the simulation platform is primarily developed for generating dynamic phantoms for emission tomography studies, it can easily be extended to accommodate dynamic MR and CT imaging simulation protocols.

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“…Optimized Boundary Detection: Since vertex correspondence is preserved during mesh adaptation, we can assign a locally optimal boundary detection function to each mesh triangle using the Simulated Search approach [10]. Specifically, the magnitude of the image gradient (projected onto the triangle normal vector) together with several additional constraints on the gray values and image characteristics across the boundary are used for boundary detection.…”

Section: Multi-stage Segmentationmentioning

confidence: 99%

Limited Angle C-Arm Tomography and Segmentation for Guidance of Atrial Fibrillation Ablation Procedures

Schäfer

Meyer

Bullens

et al. 2012

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012

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Abstract. Angiographic projections of the left atrium (LA) and the pulmonary veins (PV) acquired with a rotational C-arm system are used for 3D image reconstruction and subsequent automatic segmentation of the LA and PV to be used as roadmap in fluoroscopy guided LA ablation procedures. Acquisition of projections at high oblique angulations may be problematic due to increased collision danger of the detector with the right shoulder of the patient. We investigate the accuracy of image reconstruction and model based roadmap segmentation using limited angle C-arm tomography. The reduction of the angular range from 200• to 150• leads only to a moderate increase of the segmentation error from 1.5 mm to 2.0 mm if matched conditions are used in the segmentation, i.e. the model based segmentation is trained on images reconstructed with the same angular range as the test images. The minor decrease in accuracy may be outweighed by clinical workflow improvement, gained when large C-arm angulations can be avoided.

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Optimizing boundary detection via Simulated Search with applications to multi-modal heart segmentation

Cited by 91 publications

References 50 publications

Estimation of tissue contractility from cardiac cine-MRI using a biomechanical heart model

Estimation of tissue contractility from cardiac cine-MRI using a biomechanical heart model

A 5D computational phantom for pharmacokinetic simulation studies in dynamic emission tomography

Limited Angle C-Arm Tomography and Segmentation for Guidance of Atrial Fibrillation Ablation Procedures

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