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Segmentation is an important process especially in a Computer Aided Diagnosis (CADx) system. There are various methods of segmentation. A large majority of these involve a threshold based approach. For this study full HRCT Thorax scans from 10 normal patients were analysed. This study proposes a performance evaluation system for segmentation system. The performance evaluation uses five measures which...
Segmentation is the preliminary steps in developing a computer aided diagnosis (CAD) system. Determining the quality of segmentation will be able to minimize errors in the CAD system. Ninety-six High Resolution Computed Tomography (HRCT) thorax images in DICOM format were obtained from the Department of Diag-nostic imaging of Kuala Lumpur, Malaysia consisting of Interstitial Lung Disease (ILD) cases,...
Detection of implanted iodine-125 seeds in postoperative CT is a necessary step for evaluating the output of seed implantation brachytherapy of lung tumor. In this paper, we propose a semi-automated method to detect implanted seeds in postoperative lung CT. Three main steps are included in our approach. Firstly, the ROI (Region Of Interest) containing all seeds is extracted from the original image...
In this paper an automatic computer-aided (CAD) method is utilized for lung segmentation using computed tomography (CT) images. We segmented lung regions — based on the CT data- with nodules attached to the chest wall by using level set modeling. This method is made up of 3 steps: In the first step, an adaptive fuzzy thresholding operation is used to binarize the CT images; in the second step, the...
In the field of modern radiotherapy, in order to determine the critical organs and cancerous areas accurately various automated segmentation algorithms have been proposed. Segmentation of the lungs from computed tomography (CT) scans is an indispensable part of radiation treatment planning (RTP). Conventional lung segmentation algorithms may fail due to the low contrast between the lungs and surrounding...
This paper describes a fully automatic simultaneous lung vessel and airway enhancement filter. The approach consists of a Frangi-based multiscale vessel enhancement filtering specifically designed for lung vessel and airway detection, where arteries and veins have high contrast with respect to the lung parenchyma, and airway walls are hollow tubular structures with a non negative response using the...
In recent years, the clinical treatment of computed tomography (CT) has become an important tool in medical imaging. Usually, we can integrate the computer-aided diagnosis (CAD) system to provide the physician the more reliable vision for preoperative diagnosing and analyzing. In this study, we aim to develop a novel region-based method for segmenting lung and lung tumors by the chest CT, and to obtain...
In this paper 2D Otsu algorithm based on particle swarm optimization (PSO) is proposed to segment CT lung images. This method can extract pulmonary parenchyma from multisliced CT images, which is primary step to detect the pulmonary disease such as lung cancer, tumor, and mass cells. In the automated pulmonary disease diagnosis, image segmentation plays an important role and image analysis result...
Lung segmentation is an important first step for quantitative lung CT image analysis and computer aided diagnosis. However, accurate and automated lung CT image segmentation may be made difficult by the presence of the abnormalities. Since many lung diseases change tissue density, resulting in intensity changes in the CT image data, intensity-only segmentation algorithms will not work for most pathological...
Radiation therapy is one of the most effective options used in the treatment of about half of all people with cancer. A critical goal in radiation therapy is to deliver optimal radiation doses to the observed tumor while sparing the surrounding healthy tissues. Radiation oncologists typically manually delineate normal and diseased structures on three-dimensional computed tomography~(3D-CT) scans....
This paper deals with segmentation of the lung tissues from low dose CT (LDCT) scans of the chest. Goal is correct segmentation as well as maintaining the details of the lung region in the chest cavity. In particular, it is essential that the lung nodules inside the lungs as well as on the boundary regions be maintained for subsequent steps that aim at automatic detection and classification of nodules...
Lobewise analysis of the pulmonary parenchyma is of clinical relevance for diagnosing and monitoring pathologies. In this work, a fully automatic lobe segmentation approach is presented, which is based on a previously proposed watershed transformation approach. The proposed extension explicitly considers the pulmonary fissures by including them in the cost image for the watershed segmentation. The...
Several medical imaging techniques are used to perform the Pulmonary Embolism diagnose. Multimodality imaging is usually used to achieve better morphological details. In this work we applied and compared 3D registration algorithms, after the segmentation of thoracic CT exam, ventilation and perfusion SPECT exams. The registration routine is applied using rigid body transformations, affine transformations...
Identification of lobar fissures in human lungs is a non-trivial task due to their variable shape and appearance, along with the low contrast and high noise in computed tomographic (CT) images. Pathologies in the lungs can further complicate this identification by deforming and/or disrupting the lobar fissures. Current algorithms rely on the general anatomy of the lungs to find fissures affected by...
Identification and characterization of diffuse parenchyma lung disease patterns challenges computer aided diagnosis (CAD) schemes in computed tomography (CT). Accuracy of these preprocessing stages is expected to influence the accuracy of lung CAD schemes. Although algorithms aimed at improving the accuracy of segmentation of lung fields in presence of DPLDs have been reported, the corresponding vessel...
Conventional methods that perform lung segmentation in CT rely on a large contrast in Hounsfield units between the lung and surrounding tissues. But the segmentation of lungs affected by high density pathologies that are connected to the lung border and discontinuities in the pixel intensities may be caused by X-ray projecting intensity changes, differing tissue reflectance and transmission properties,...
A pleural effusion is a condition where there is a buildup of abnormal fluid within the pleural space. This paper presents an automated method to evaluate the severity of pleural effusion using regular chest CT images. First the lungs are segmented using region growing, mathematical morphology and anatomical knowledge. Then the visceral and parietal layers of the pleura are extracted based on anatomical...
In this paper we have proposed a method for lungs nodule detection from computed tomography (CT) scanned images by using Fuzzy C-Mean (FCM) and morphological techniques. First of all, fuzzy have been used for automated segmentation of lungs. Region of interests (ROIs) have been extracted by using 8 directional searches slice by slice and then 3D ROI image have been constructed. A 3D template has been...
In this paper problem of airway tree segmentation from CT data sets was regarded. The idea of segmentation using 3D seeded region growing algorithm was introduced. Common problems arising during extracting airway tree from CT data using region growing method were explained. Especially problem of leakage from airway into the lung parenchyma was outlined. Common methods of CT data sets preprocessing...
Segmentation is considered an essential step in medical image analysis and classification. In this paper we describe a method for lung segmentation based on Genetic Algorithm (GA) and morphological image processing techniques. We have used Genetic Algorithm to determine the threshold. The proposed system is able to perform fully automatic segmentation of CT scanned lung images. The proposed system...
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