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The segmentation of cervical vertebra in X-Ray radiographs can give valuable information for the study of the vertebral mobility. One particular characteristic of the X-Ray images is that they present very low grey level variation and makes the segmentation difficult to perform. In this paper, we propose a segmentation procedure based on the Active Shape Model to deal with this issue. However, this...
The purpose of this work is to compute several image processing techniques, applied to US images of HIFU-induced lesions, to characterize the shape, contour, position and the orientation of thermal lesions. In order to obtain real-time monitoring of HIFU treatment, a B-mode US imaging system and HIFU were synchronized. First, the HIFU sonication procedure consisted of applying an initial power of...
Laboratory tests and clinical analysis is a must to confirm or reject some medical diagnosis. Common analytical fields of knowledge are: Hematology, Clinical biochemistry, Urology, Microbiology among others. This work is for the clinical field of Hematology where detection of immature leukocytes on peripheral blood sample is part of a clinical test of relevance for detection of certain types of cancer...
This paper presents a new automatic initialization procedure for a level-set based segmentation algorithm that works on all slices for a given CT dataset. Level set segmentation algorithms provide promising results, are robust to dataset variations and do not require prior training. As such, they can be reliably used for segmentation of major organs in abdominal CT scans. However, level set algorithms...
Magnetic resonance imaging of articular cartilage has recently been recognized as the best non-invasive tool to visualize the cartilage morphology, biochemistry and function. In this paper, the challenging issue of automatic determining the cartilage volume is tackled. First, algorithms based on classical segmentation methods such as thresholding, poly-fitting, and average weight calculating are combined...
In this paper we address the problem of automatic selection of important vessel-depicting key frames within 2D angiography videos. Two different methods of frame selection are described, one based on Frangi filter, and the other based on detecting parallel curves formed from edges in angiography images. Results are shown by comparison to physician annotation of such key frames on 2D coronary angiograms.
When using deformable models for the segmentation of biological data, the choice of the best weighting parameters for the internal and external forces is crucial. Especially when dealing with 3D fluorescence microscopic data and cells within dense tissue, object boundaries are sometimes not visible. In these cases, one weighting parameter set for the whole contour is not desirable. We are presenting...
In this paper, we present a method for cup boundary detection from monocular colour fundus image to help quantify cup changes. The method is based on anatomical evidence such as vessel bends at cup boundary, considered relevant by glaucoma experts. Vessels are modeled and detected in a curvature space to better handle inter-image variations. Bends in a vessel are robustly detected using a region of...
The quality of the lung nodule models determines the success of lung nodule detection. This paper describes aspects of our data-driven approach for modeling lung nodules using the texture and shape properties of real nodules to form an average model template per nodule type. The ELCAP low dose CT (LDCT) scans database is used to create the required statistics for the models based on modern computer...
Bone mineral density (BMD) measurements and fracture analysis of the spine bones are restricted to the Vertebral bodies (VBs). In this paper, we propose a novel 3D shape based method to segment VBs in clinical computed tomography (CT) images without any user intervention. The proposed method depends on both image appearance and shape information. 3D shape information is obtained from a set of training...
An endoscope is a medical instrument that acquires images inside the human body. An endoscope carries its own light source. Classic shape-from-shading can be used to recover the 3-D shape of objects in view. Recent implementations have used the Fast Marching Method (FMM). Previous FMM approaches recover 3-D shape under assumptions of parallel light source illumination and orthographic projection....
A new speed function to guide evolution of a level-set based active contour is proposed for segmenting an object from its background in a given image. The guidance accounts for a learned spatially variant statistical shape prior, 1st-order visual appearance descriptors of the contour interior and exterior (associated with the object and background, respectively), and a spatially invariant 2nd-order...
The key step of a computer-assisted screening system that aims early diagnosis of cervical cancer is the accurate segmentation of cells. In this paper, we propose a two-phase approach to cell segmentation in Pap smear test images with the challenges of inconsistent staining, poor contrast, and overlapping cells. The first phase consists of segmenting an image by a non-parametric hierarchical segmentation...
Dynamic magnetic resonance imaging MRI acquisitions are used in the clinical assessment of the pelvic organs behaviour during an abdominal strain. The main organs (bladder, uterus-vagina, rectum) undergo deformations and intrinsic movements along a sequence. Anatomical references and measurements are generally used by clinicians to evaluate pathology grades. In this context, we have established quantitative...
Gradient vector flow snakes are a very common method in bio-medical image segmentation. The use of gradient vector flow herein brings some major advantages like a large capture range and a good adaption of the snakes in concave regions. In some cases though, the application of gradient vector flow can also have undesired effects, e.g. if only parts of an image are strongly blurred, the remaining weak...
Attribute filters allow enhancement and extraction of features without distorting their borders, and never introduce new image features. These are highly desirable properties in biomedical imaging, where accurate shape analysis is paramount. However, setting the attribute-threshold parameters has to date only been done manually. This paper explores simple, fast and automated methods of computing attribute...
In this paper we propose a supervised 3D segmentation algorithm to locate the esophagus in thoracic CT scans using a variational framework. To address challenges due to low contrast, several priors are learned from a training set of segmented images. Our algorithm first estimates the centerline based on a spatial model learned at a few manually marked anatomical reference points. Then an implicit...
Dyslexia severely impairs learning abilities, so that improved diagnostic methods are called for. Neuropathological studies have revealed abnormal anatomy of the Corpus Callosum (CC) in dyslexic brains. We explore a possibility of distinguishing between dyslexic and normal (control) brains by quantitative CC shape analysis in 3D magnetic resonance images (MRI). Our approach consists of the three steps:...
In this paper, a statistical texture modeling method is proposed for medical volumes. As the shapes of the human organ are very different from one case to another, 3D volume morphing is applied to normalize all the volume datasets to a same shape for removing shape variations. In order to deal with the problems of high-dimension and small number of medial samples, we propose an effective image compression...
Computer assisted medical image processing can extract vital information that may be elusive to human eyes. In this paper, an algorithm is proposed to automatically estimate the position of the actual midline from the brain CT scans using multiple regions shape matching. The method matches feature points identified from a set of ventricle templates, extracted from MRI, with the corresponding feature...
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