Abstract：
:This paper presents a robust algorithm for calibration and system registration of endoscopic imaging devices. The system registration allows us to map accurately each point in the world coordinate system into the endoscope image and vice versa to obtain the world line of sight for each image pixel. The key point of our system is a robust linear algorithm based on singular value decomposition (SVD) for estimating simultaneously two unknown coordinate transformations. We show that our algorithm is superior in terms of robustness and computing efficiency to iterative procedures based on Levenberg-Marquardt optimization or on quaternion approaches. The algorithm does not require the calibration pattern to be tracked. Experimental results and simulations verify the robustness and usefulness of our approach. They give an accuracy of less than 0.7 mm and a success rate >99%. We apply the calibrated endoscope to the neurosurgical relevant case of red out, where in spite of the complete loss of vision the surgeon gets visual aids in the endoscope image at the actual position, allowing him/her to manoeuvre a coagulation fibre into the right position. Finally, we outline how our registration algorithm can be used also for standard registration applications (establish the mapping between two sets of points). We propose our algorithm as a linear, non-iterative algorithm also for projective transformations and for 2D-3D-mappings. Thus, it can be seen as a generalization of the well-known Umeyama registration algorithm.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Konen W,Tombrock S,Scholz Mdoi
10.1016/j.media.2007.04.006subject
Has Abstractpub_date
2007-12-01 00:00:00pages
526-39issue
6eissn
1361-8415issn
1361-8423pii
S1361-8415(07)00043-6journal_volume
11pub_type
杂志文章abstract：:Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is a crucial step for radiation therapy in the treatment of prostate cancer. However, it is a very challenging task due to unclear boundaries, large intra- and inter-patient shape variability, and uncertain existence of bo...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.03.003
更新日期：2019-05-01 00:00:00
abstract：:Many cardiac pathologies are reflected in abnormal myocardial deformation, accessible through magnetic resonance tagging (MRT). Interpretation of the MRT data is difficult, since the relation between pathology and deformation is not straightforward. Mathematical models of cardiac mechanics could be used to translate m...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2006.04.001
更新日期：2006-08-01 00:00:00
abstract：:Accurate and robust segmentation of abdominal organs on CT is essential for many clinical applications such as computer-aided diagnosis and computer-aided surgery. But this task is challenging due to the weak boundaries of organs, the complexity of the background, and the variable sizes of different organs. To address...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.04.005
更新日期：2019-07-01 00:00:00
abstract：:This paper describes a new robust and fully automatic method for calibration of three-dimensional (3D) freehand ultrasound called Confhusius (CalibratiON for FreeHand UltraSound Imaging USage). 3D Freehand ultrasound consists in mounting a position sensor on a standard probe. The echographic B-scans can be localized i...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2004.06.021
更新日期：2005-02-01 00:00:00
abstract：:The Cartesian parallel magnetic imaging problem is formulated variationally using a high-order penalty for coil sensitivities and a total variation like penalty for the reconstructed image. Then the optimality system is derived and numerically discretized. The objective function used is non-convex, but it possesses a ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.07.002
更新日期：2012-01-01 00:00:00
abstract：:Magnetic resonance imaging is a popular and powerful non-invasive imaging technique. Automated analysis has become mandatory to efficiently cope with the large amount of data generated using this modality. However, several artifacts, such as intensity non-uniformity, can degrade the quality of acquired data. Intensity...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.09.004
更新日期：2006-04-01 00:00:00
abstract：:Sulcal pits are the points of maximal depth within the folds of the cortical surface. These shape descriptors give a unique opportunity to access to a rich, fine-scale representation of the geometry and the developmental milestones of the cortical surface. However, using sulcal pits analysis at group level requires ne...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101749
更新日期：2020-12-01 00:00:00
abstract：:Human brain alignment based on imaging data has long been an intriguing research topic. One of the challenges is the huge inter-individual variabilities, which are pronounced not only in cortical folding patterns, but also in the underlying structural and functional patterns. Also, it is still not fully understood how...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101700
更新日期：2020-07-01 00:00:00
abstract：:We introduce a new approach to medical image analysis that combines deformable model methodologies with concepts from the field of artificial life. In particular, we propose "deformable organisms", autonomous agents whose task is the automatic segmentation, labeling, and quantitative analysis of anatomical structures ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(02)00083-x
更新日期：2002-09-01 00:00:00
abstract：:Images of the retina acquired using optical coherence tomography (OCT) often suffer from intensity inhomogeneity problems that degrade both the quality of the images and the performance of automated algorithms utilized to measure structural changes. This intensity variation has many causes, including off-axis acquisit...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.09.008
更新日期：2018-01-01 00:00:00
abstract：:Registration of three-dimensional ultrasound (3DUS) volumes is necessary in several applications, such as when stitching volumes to expand the field of view or when stabilizing a temporal sequence of volumes to cancel out motion of the probe or anatomy. Current systems that register 3DUS volumes either use external tr...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.10.004
更新日期：2012-02-01 00:00:00
abstract：:Highly relevant for both clinical and legal medicine applications, the established radiological methods for estimating unknown age in children and adolescents are based on visual examination of bone ossification in X-ray images of the hand. Our group has initiated the development of fully automatic age estimation meth...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101538
更新日期：2019-12-01 00:00:00
abstract：:The availability of a large amount of annotated data is critical for many medical image analysis applications, in particular for those relying on deep learning methods which are known to be data-hungry. However, annotated medical data, especially multimodal data, is often scarce and costly to obtain. In this paper, we...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101565
更新日期：2020-01-01 00:00:00
abstract：:Alzheimers disease (AD) is a complex neurodegenerative disease. Its early diagnosis and treatment have been a major concern of researchers. Currently, the multi-modality data representation learning of this disease is gradually becoming an emerging research field, attracting widespread attention. However, in practice,...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101953
更新日期：2021-01-01 00:00:00
abstract：:We propose a novel airway segmentation method in volumetric chest computed tomography (CT) and evaluate its performance on multiple datasets. The segmentation is performed voxel-by-voxel by a 2.5D convolutional neural net (2.5D CNN) trained in a supervised manner. To enhance the accuracy of the segmented airway tree, ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.10.006
更新日期：2019-01-01 00:00:00
abstract：:Temporal correlation in dynamic magnetic resonance imaging (MRI), such as cardiac MRI, is informative and important to understand motion mechanisms of body regions. Modeling such information into the MRI reconstruction process produces temporally coherent image sequence and reduces imaging artifacts and blurring. Howe...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101901
更新日期：2021-02-01 00:00:00
abstract：:Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or a...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.12.004
更新日期：2016-04-01 00:00:00
abstract：:Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-consuming and unreliable) which is currently the gold standard for AIS...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.05.005
更新日期：2018-08-01 00:00:00
abstract：:In this work we propose a comprehensive study of Digital Stent Enhancement (DSE), from the analysis of the requirements to the validation of the proposed solution. First, we derive the stent visualization requirements in the context of the clinical application and workflow. Then, we propose a DSE algorithm combining a...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.03.002
更新日期：2011-08-01 00:00:00
abstract：:This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SI...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.11.001
更新日期：2012-04-01 00:00:00
abstract：:Diffusion tensor imaging can provide the fundamental information required for viewing structural connectivity. However, robust and accurate acquisition and processing algorithms are needed to accurately map the nerve connectivity. In this paper, we present a novel algorithm for extracting and visualizing the fiber tra...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2003.12.001
更新日期：2004-06-01 00:00:00
abstract：:Image-based parcellation of the brain often leads to multiple disconnected anatomical structures, which pose significant challenges for analyses of morphological shapes. Existing shape models, such as the widely used spherical harmonic (SPHARM) representation, assume topological invariance, so are unable to simultaneo...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.02.004
更新日期：2015-05-01 00:00:00
abstract：:In this paper, we exploit the ability of Compressed Sensing (CS) to recover the whole 3D Diffusion MRI (dMRI) signal from a limited number of samples while efficiently recovering important diffusion features such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF). Some attempts to...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.02.010
更新日期：2013-07-01 00:00:00
abstract：:An automated vendor-independent system for dose monitoring in computed tomography (CT) medical examinations involving ionizing radiation is presented in this paper. The system provides precise size-specific dose estimates (SSDE) following the American Association of Physicists in Medicine regulations. Our dose managem...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101898
更新日期：2021-02-01 00:00:00
abstract：:The spinal column is one of the most distinguishable structures in CT scans of the superior part of the human body. It is not necessary to segment the spinal column in order to use it as a frame of reference. It is sufficient to place landmarks and the appropriate anatomical labels at intervertebral disks and vertebra...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.07.005
更新日期：2013-12-01 00:00:00
abstract：:With the advent of large-scale imaging studies and big health data, and the corresponding growth in analytics, machine learning and computational image analysis methods, there are now exciting opportunities for deepening our understanding of the mechanisms and characteristics of heart disease. Two emerging fields are ...
journal_title：Medical image analysis
pub_type： 社论,评审
doi：10.1016/j.media.2016.06.027
更新日期：2016-10-01 00:00:00
abstract：:The accurate localization of anatomical landmarks is a challenging task, often solved by domain specific approaches. We propose a method for the automatic localization of landmarks in complex, repetitive anatomical structures. The key idea is to combine three steps: (1) a classifier for pre-filtering anatomical landma...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.02.004
更新日期：2013-12-01 00:00:00
abstract：:In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.12.006
更新日期：2011-06-01 00:00:00
abstract：:Segmentation of the geometric morphology of abdominal aortic aneurysm is important for interventional planning. However, the segmentation of both the lumen and the outer wall of aneurysm in magnetic resonance (MR) image remains challenging. This study proposes a registration based segmentation methodology for efficien...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.05.005
更新日期：2017-08-01 00:00:00
abstract：:The problem of respiratory motion has proved a serious obstacle in developing techniques to acquire images or guide interventions in abdominal and thoracic organs. Motion models offer a possible solution to these problems, and as a result the field of respiratory motion modelling has become an active one over the past...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2012.09.005
更新日期：2013-01-01 00:00:00
