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In the recent years, reconstructing 3D liver and its vessels from abdominal CT volume images becomes an inevitable and necessary research field. In this paper, a method of 3D reconstruction of liver with its vessels has been implemented, which involves volume preprocessing, de-noising, segmentation, contouring, and combination of different modalities. An advanced liver segmentation algorithms have...
Accurate prostate localization is the key to the success of radiotherapy. It remains a difficult problem for CT images due to the low image contrast, the prostate motion, and the uncertain presence of rectum gas. In this paper, a learning based framework is proposed to improve the accuracy of prostate detection in CT. It adaptively determines distinctive feature types at distinctive image regions,...
Incorporating biomedical information into nonrigid image registration is an important approach to improve the registration quality and provide realistic results. However, previous tissue-dependent deformation field filtering incur a relatively high computation cost in order to obtain results of improved quality. In this paper, we propose a collapsed-cone based adaptive filtering method to reduce the...
In the context of vessel tree structures segmentation with implicit deformable models, we propose to exploit convolution surfaces to introduce a novel variational formulation, robust to bifurcations, tangential vessels and aneurysms. Vessels are represented by an implicit function resulting from the convolution of the centerlines of the vessels, modeled as a second implicit function, with localized...
Micro-tomography produces high resolution images of biological structures such as vascular networks. In this paper, we present a new approach for segmenting vascular network into pathological and normal regions from considering their micro-vessel 3D structure only. We define and use a conditional random field for segmenting the output of a watershed algorithm. The tumoral and normal classes are thus...
To diagnose the osteoporosis accurately, the bone mineral density (BMD) measurements of the vertebral bodies (VBs) are required. In this paper, we propose a new segmentation and registration method in order to assist the BMD measurements and fracture analysis (FA) accurately. In this experiment, image appearance and shape information of VBs are used. Our shape model is required to be registered to...
Quantitative assessment of facial asymmetry is crucial for successful planning of corrective surgery. We propose a tensor-based morphometry (TBM) framework to locate and quantify asymmetry using 3D CBCT images. To this end, we compute a rigid transformation between the mandible segmentation and its mirror image, which yields global rotation and translation with respect to the cranial base to guide...
Computed Tomography Angiography (CTA) of the heart is a non-invasive procedure to rule out coronary artery disease or measure its extent and plan treatments and interventions. The need for coronary tree tracking methods that require minimum human interaction and produce accurate and robust measurements is therefore of great clinical importance. In this work we present a probabilistic coronary artery...
Pancreas segmentation in 3-D computed tomography (CT) data is of high clinical relevance, but extremely difficult since the pancreas is often not visibly distinguishable from the small bowel. So far no automated approach using only single phase contrast enhancement exist. In this work, a novel fully automated algorithm to extract the pancreas from such CT images is proposed. Discriminative learning...
While many computer-aided detection (CADe) systems for CT colonography can detect polypoid lesions at a high sensitivity level, very few are targeted toward detecting flat lesions. Research has shown that flat lesions are more likely to contain carcinoma than polypoid lesions; therefore, it is imperative that they be adequately detected in screenings and examinations. However, current CADe systems...
An automatically extracted 2d contour of a lymph node in a single CT slice is required for size assessment as well as for the initialization of model based 3d lymph node segmentation algorithms. This paper presents a novel single slice lymph node segmentation approach. It finds a closed path around a seed point thereby minimizing an energy function which depends on gradients, intensities and shape...
We present a simple and elegant method to incorporate user input in a template-based segmentation method for diseased organs. The user provides a partial segmentation of the organ of interest, which is used to guide the template towards its target. The user also highlights some elements of the background that should be excluded from the final segmentation. We derive by likelihood maximization a registration...
Statistical shape and intensity modelling have been subject to an increasing interest within the past decade. However, construction of such models requires large number of segmented examples. Accurate and automatic segmentation techniques that do not require any explicit prior model are therefore of high interest. We propose a fully-automatic method for segmenting the femur in 3D Computed Tomography...
Chest pathology can lead to airway branch obstruction, and segmentation of the airways beyond obstructions is a challenge. We propose a novel method that automatically identifies points of obstruction using airway topology and statistical shape analysis and segments disconnected branches. The point of obstruction is used to define an allowed region for the airway beyond the obstruction in order to...
The microscopic pore structure is the base platform of the pore-scale microscopic percolation mechanism research. This paper is mainly to introduce the micro-CT scanning method for the construction of digital cores and the maximal ball algorithm for the establishment of pore network. For the micro-CT scanning method, we first use micro-CT scanning to get core projection data, and then adopt the FDK...
The liver is a common site for the occurrence of tumors. Automatic hepatic lesion segmentation is a crucial step for diagnosis and surgery planning. This paper presents a new fully automatic technique to segment the tumors in liver structure with no interaction from user. Contrast enhancement is applied to the slices of segmented liver, then adding each image to itself to have a white image with some...
Partially regularized technique is an extension based on interval constraint of minimum norm solution. Such techniques have shown good results on problems like Missing Data Recovery (MDR). The proposed use of partially regularized technique for the computer tomography (CT) image reconstruction is to investigate if the MDR concept can be used for few view projection data acquisition scenario. The motivation...
An ultra-resolution high-sensitivity preclinical PET/CT - MuPET is designed and manufactured. The detector system is a triacontagon shape which is very close to a perfect cylindrical ring. The inner diameter of the ring is 165 mm and the axial length is 116 mm. The detector system is using 180 PMT-quadrant-sharing (PQS) blocks - 30 blocks per ring and 6 rings axially with 210 low-cost round PMTs for...
It is easy to segment the liver with existing methods using both basic place information (the liver exists on the left of the abdominal CT image) and distribution information of regular gray values. However, the existing methods can not be used for segmenting an abnormal liver. Because the gray values of lesions do not show the original gray values of the liver, lesion parts of the abnormal liver...
Automated liver segmentation is problematic due to variations in liver shape / size and because the liver has a similar density distribution to surrounding structures. We propose a method that: 1) utilizes iteratively constructed probabilistic liver and rib cage atlases, 2) conducts the Gaussian distribution analysis to avoid incorrectly classifying the irrelevant surrounding tissues as `liver region'...
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