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检索条件"任意字段=5th International Conference on Medical Image Computing and Computer-Assisted Intervention"

共 2882 条记录，以下是2631-2640 订阅

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Automated white matter lesion segmentation by voxel probability estimation

Automated white matter lesion segmentation by voxel probabil...

引用

6th international conference on medical image computing and computer-assisted intervention

作者： Anbeek, P Vincken, K van Osch, M Bisschops, B Viergever, M van der Grond, J Univ Utrecht Med Ctr Dept Radiol Image Sci Inst Utrecht Netherlands

ISBN: (纸本)3540204628

A new method for fully automated segmentation of white matter lesions (WMLs) on cranial MR imaging is presented. the algorithm uses five types of regular MRI-scans. It is based on a k-Nearest Neighbor (KNN) classification technique, which builds a feature space from voxel intensities and spatial information. the technique generates images representing the probability per voxel being part of a WML. By application of thresholds on these probability maps binary segmentations are produced. ROC-curves show that the segmentations achieve high sensitivity and specificity. the similarity index (SI) is used for further analysis and for determination of the optimal threshold. the probabilistic equivalent of the SI allows direct evaluation of the probability maps, which provides a strong tool for comparison of different classification results. this method for automated WML segmentation reaches an accuracy that is comparable to methods for multiple sclerosis lesion segmentation.

关键词： image segmentation

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Camera model and calibration procedure for oblique-viewing endoscope 1

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6th international conference on medical Imaging computing and computer-assisted intervention

作者： Yamaguchi, T Nakamoto, M Sato, Y Nakajima, Y Konishi, K Hashizume, M Nishii, T Sugano, N Yoshikawa, H Yonenobu, K Tamura, S Osaka Univ Grad Sch Med Div Interdisciplinary Image Anal Suita Osaka 565 Japan Osaka Univ Grad Sch Med Dept Orthopaed Surg Suita Osaka 565 Japan Kyushu Univ Grad Sch Med Sci Fukuoka 812 Japan Osaka Minami Natl Hosp Osaka Japan

ISBN: (数字)9783540399032

ISBN: (纸本)3540204644

Oblique-viewing endoscopes (oblique scopes) are widely used medically. It is essential for certain procedures such as laparoscopy, arthroscopy, and sinus endoscopy. In an oblique scope, its viewing directions are changeable by rotating the scope cylinder. Although a camera calibration method is necessary to apply augmented reality technologies to oblique endoscopic procedures, no method for oblique scope calibration has been developed yet. In the present paper, we formulate a camera model and a calibration procedure for oblique scopes. In the calibration procedure, Tsai's calibration is performed at zero-rotation of the scope cylinder, and then the variation of the external camera parameters corresponding to the rotation of the scope cylinder is modeled and estimated as a function of the rotation angle. Accurate estimation of the rotational axis is included in the procedure. the precision of this estimation was demonstrated to have a significant effect on the overall calibration accuracy in the experimental evaluation especially with large rotation angles. the projection error in the image plane was around two pixels. the proposed method was shown to be clinically applicable.

关键词： Rotation

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Vascular atlas formation using a vessel-to-image affine registration method

Vascular atlas formation using a vessel-to-image affine regi...

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6th international conference on medical Imaging computing and computer-assisted intervention

作者： Chillet, D Jomier, J Cool, D Aylward, S Univ N Carolina Dept Radiol Comp Aided Diag & Display Lab Chapel Hill NC 27515 USA Ecole Super Chim Phys Lyon F-69100 Lyon France

ISBN: (纸本)3540204628

We have developed a method for forming vascular atlases using vascular distance maps and a novel vascular model-to-image registration method. Our atlas formation process begins with MR or CT angiogram data from a set of subjects. We extract blood vessels from those data using our tubular object segmentation method. One subject's vascular network model is then chosen as a template, and its vascular distance map (DM) image is computed. Each of the remaining vascular network models is then registered with the DM template using our vascular model-to-image affine registration method. the DM images from the registered vascular models are then computed. the mean and variance images formed from those registered DM images are the vascular atlas. In this paper we apply the atlas formation process to build atlases of normal brain and liver vasculature. We use Monte Carlo simulations to demonstrate the reliability of the underlying registration method. Additionally, we explain the clinical potential of those atlases and conduct z-score analyses to compare individuals with the atlases to detect abnormal vessels.

关键词： medical imaging

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Cardiac LV segmentation using a 3D active shape model driven by fuzzy inference

Cardiac LV segmentation using a 3D active shape model driven...

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6th international conference on medical image computing and computer-assisted intervention

作者： van Assen, HC Danilouchkine, MG Behloul, F Lamb, HJ van der Geest, RJ Reiber, JHC Lelieveldt, BPF Leiden Univ Med Ctr Dept Radiol Div Image Proc NL-2300 RC Leiden Netherlands

ISBN: (纸本)3540204628

Manual quantitative analysis of cardiac left ventricular function using multi-slice CT is labor intensive because of the large datasets. In previous work, an intrinsically three-dimensional segmentation method for cardiac CT images was presented based on a 3D Active Shape Model (3D-ASM). this model systematically overestimated left ventricular volume and underestimated blood pool volume, due to inaccurate estimation of candidate points during the model update steps. In this paper, we propose a novel ASM candidate point generation method based on a Fuzzy Inference System (FIS), which uses image patches as an input. Visual and quantitative evaluation of the results for 7 out of 9 patients shows substantial improvement for endocardial contours, while the resulting volume errors decrease considerably (blood pool: -39 +/- 29 cubic voxels in the previous model, -0.66 +/- 6.2 cubic voxels in the current). Standard deviation of the epicardial volume decreases by approximately 50%.

关键词： Cardiology

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Temporal lobe epilepsy lateralization based on MR image intensity and registration features

Temporal lobe epilepsy lateralization based on MR image inte...

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6th international conference on medical image computing and computer-assisted intervention

作者： Duchesne, S Bernasconi, N Janke, A Bernasconi, A Collins, DL McGill Univ Montreal Neurol Inst Montreal PQ H3A 2T5 Canada Univ Queensland Ctr Magnet Resonance Brisbane Qld Australia

ISBN: (纸本)3540204628

In the context of MR imaging, explicit segmentation followed by stereologic volumetry of the hippocampus (HC) has been the standard approach toward temporal lobe epilepsy (TLE) lateralization of the seizure focus. the novelty of the method presented here resides in its analysis of characteristics of large, non-specific Volumes of Interest from T1 MRI data aiming to lateralize the seizure focus in patients with TLE without segmentation. For this purpose, Principal Components Analysis (PCA) of two image features are united to create a multi-dimensional space representative of a training set population composed of 150 normal subjects. the feature instances consist of grey-level intensity and an approximation of the Jacobian matrix of non-linear registration-derived dense deformation fields. New data for TLE subjects are projected in this space, under the assumption that the distributions of the projections of normal and patients are not identical and can be used for lateralization. Results are presented following PCA modeling of the left medial temporal lobe only for all subjects. It is shown that linear discriminant analysis of the eigencoordinates can be used to lateralize the seizure focus in TLE patients with a 75% accuracy. It is expected that adding a right temporal lobe model will improve lateralization results beyond those of HC volumetry.

关键词： MR intensity non-linear deformation fields jacobian matrices principal components analysis linear discriminant

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ImLib3D: An efficient, open source, medical image processing framework in C++ 1

引用

medical image computing and computer-assisted intervention, MICCAI 2003 - 6th international conference Proceedings

作者： Bosc, Marcel Vik, Torbjorn Armspach, Jean-Paul Heitz, Fabrice LSIIT UMR-7005 CNRS Strasbourg I University 67400 Illkirch France IPB UMR-7004 CNRS Strasbourg I University 67085 Strasbourg France

ISBN: (数字)9783540399032

ISBN: (纸本)9783540204640

ImLib3D is a C++ library for 3D medical image processing research. It provides a carefully designed, object-oriented, standards conforming C++ library, as well as a separate visualization system. Focus has been put on simplicity for the researcher who is considered to be the end-user. Source code is freely available and has been placed in an open collaborative development environment.

关键词： image processing

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Generalized image models and their application as statistical models of images

Generalized image models and their application as statistica...

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medical image computing and computer-assisted intervention, MICCAI 2003 - 6th international conference Proceedings

作者： Ángel, Miguel Ballester, Gonzalez Pennec, Xavier Ayache, Nicholas Epidaure Project INRIA Sophia Antipolis France

A generalized image model (GIM) is presented. images are represented as sets of 4-dimensional sites combining position and intensity information, as well as their associated uncertainty and joint variation, this model seamlessly allows for the representation of both images and statistical models, as well as other representations such as landmarks or meshes. A GIM-based registration method aimed at the construction and application of statistical models of images is proposed. A procedure based on the iterative closest point (ICP) algorithm is modified to deal with features other than position and to integrate statistical information. Furthermore, we modify the ICP framework by using a Kalman filter to efficiently compute the transformation. the initialization and update of the statistical model are also described. V.

关键词： image analysis

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Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm

Segmentation of 4D cardiac MR images using a probabilistic a...

引用

6th international conference on medical image computing and computer-assisted intervention

作者： Lorenzo-Valdés, M Sanchez-Ortiz, GI Mohiaddin, R Rueckert, D Univ London Imperial Coll Sci Technol & Med Dept Comp Visual Informat Proc Grp London SW7 2BZ England Royal Brompton & Harefield NHS Trust London England

ISBN: (纸本)3540204628

In this paper an automatic atlas-based segmentation algorithm for 4D cardiac MR images is proposed. the algorithm is based on the 4D extension of the expectation maximisation (EM) algorithm. the EM algorithm uses a 4D probabilistic cardiac atlas to estimate the initial model parameters and to integrate a-priori information into the classification process. the probabilistic cardiac atlas has been constructed from the manual segmentations of 3D cardiac image sequences of 14 subjects. It provides space and time-varying probability maps for the left and right ventricle, the myocardium, and background structures such as the liver, stomach, lungs and skin. In addition to the probabilistic cardiac atlas, the segmentation algorithm incorporates spatial and temporal contextual information by using 4D Markov Random Fields (MRF). Validation against manual segmentations and computation of the correlation between manual and automatic segmentation on 249 3D volumes were calculated. Results show that the procedure can successfully segment the left ventricle (LV) (r=0.95), myocardium (r=0.83) and right ventricle (RV) (r=0.91).

关键词： image segmentation

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ICA vs. PCA active appearance models:: Application to cardiac MR segmentation

ICA vs. PCA active appearance models:: Application to cardia...

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6th international conference on medical image computing and computer-assisted intervention

作者： Üzümcü, M Frangi, AF Sonka, M Reiber, JHC Lelieveldt, BPF Leiden Univ Med Ctr Dept Radiol Div Image Proc Leiden Netherlands Univ Zaragoza Div Biomed Engn Aragon Inst Engn Res Zaragoza Spain Univ Iowa Dept Elect & Comp Engn Iowa City IA 52242 USA

ISBN: (纸本)3540204628

Statistical shape models generally use Principal Component Analysis (PCA) to describe the main directions of shape variation in a training set of example shapes. However, PCA has the restriction that the input data must be drawn from a Gaussian distribution and is only able to describe global shape variations. In this paper we evaluate the use of an alternative shape decomposition, Independent Component Analysis (ICA), for two reasons. ICA does not require a Gaussian distribution of the input data and is able to describe localized shape variations. With ICA however, the resulting vectors are not ordered, therefore a method for ordering the Independent Components is presented in this paper. To evaluate ICA-based Active Appearance Models (AAMs), 10 leave-15-out models were trained on a set of 150 short-axis cardiac MR images with PCA-based as well as ICA-based AAMs. the median values for the average and maximal point-to-point distances between the expert drawn and automatically segmented contours for the PCA-based AAM were 2.95 and 8.39 pixels. For the ICA-based AAM these distances were 1.86 and 5.01 pixels respectively. From this, we conclude that the use of ICA results in a substantial improvement in border localization accuracy over a PCA-based model.

关键词： Principal component analysis

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Brachytherapy seed localization from fluoroscopic images using a statistical classifier

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6th international conference on medical image computing and computer-assisted intervention, MICCAI 2003

作者： Su, Yi Davis, Brian J. Herman, Michael G. La Joie, Wayne N. Robb, Richard A. Mayo Clinic and Foundation RochesterMN55905 United States

ISBN: (纸本)3540204644

A method to determine the number and location of seed images in clusters on a fluoroscopic image was developed based on a statistical analysis of cluster size in simulated fluoroscopic images. A modified 3-film technique was used to reconstruct the 3D positions of seeds from their image locations. Preliminary results suggest that this new method can identify all the seeds and localize them to an average precision of 0.55 mm. this is an important step toward intraoperative radiation dose analysis. © Springer-Verlag Berlin Heidelberg 2003.

关键词： image classification

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