A Hybrid Approach for Automatic Aorta Segmentation in Abdominal 3D CT Scan Images

2021 ◽  
Vol 11 (3) ◽  
pp. 712-719
Author(s):  
Iftikhar Ahmad ◽  
Sami ur Rehman ◽  
Imran Ullah Khan ◽  
Arfa Ali ◽  
Hussain Rahman ◽  
...  
Keyword(s):  
Medical Imaging ◽  
Ct Scan ◽  
Hybrid Approach ◽  
Computational Cost ◽  
Iterative Algorithms ◽  
Fast Algorithms ◽  
Human Anatomy ◽  
3D Ct Scan ◽  
Segmentation Accuracy ◽  
Segmentation Algorithms

Due to rapid advancement in medical imaging, human anatomy is now observable in finer details bringing new dimensions to diagnosis and treatment. One such area which benefitted from advancement in medical imaging is aorta segmentation. Aorta segmentation is achieved by using anatomical features (shape and position of aorta) using specialized segmentation algorithms. These segmentation algorithms are broadly classified into two categories. The first type comprises of fast algorithms which exploits spatial and intensity properties of images. The second type are iterative algorithms which use optimization of a cost function to track aorta boundaries. Fast algorithms offer lower computation cost, whereas iterative algorithms offer better segmentation accuracy. Therefore, there is a tradeoff between segmentation accuracy and computational cost. In this work, a hybrid approach for aorta segmentation in 3D Computed Tomography (CT) scan images is proposed. The proposed approach produces high segmentation accuracy of intensity based (fast) approaches at reduced computational cost. The proposed technique is evaluated using real world 3D abdominal CT scan images. The proposed approach can either be used as a fast-standalone segmentation procedure, or as a pre-segmentation procedure for iterative and more accurate approaches.

scholarly journals Clinicoradiologic Evaluation of Eagle’s Syndrome and its Management

2015 ◽  
Vol 11 (4) ◽  
pp. 305-309 ◽  
Author(s):  
M Pokharel ◽  
S Karki ◽  
I Shrestha ◽  
BL Shrestha ◽  
K Khanal ◽  
...  
Keyword(s):  
Ct Scan ◽  
Styloid Process ◽  
History Taking ◽  
3D Ct ◽  
Ct Reconstruction ◽  
Eagle’S Syndrome ◽  
Elongated Styloid Process ◽  
Intraoral Approach ◽  
3D Ct Scan ◽  
Significant Difference

Background Eagle’s syndrome (Elongated styloid process) is often misdiagnosed due to its vague symptomatology. The diagnosis relies on detail history taking, palpation of styloid process in tonsillar fossa and imaging modalities.Objective To assess the length and medial angulation of elongated styloid process with the help of three dimensional computed tomography (3D CT) scan and to describe our clinical and surgical experience with patients suffering from Eagle’s syndrome.Method Prospective, analytical study conducted from August 2011 to August 2012 among 39 patients with Eagle’s syndrome. Detailed history taking, clinical examination and 3D CT scan was performed. Length and medial angulation was calculated. Patients with styloid process length longer than 2.50 cm underwent surgical excision via intraoral approach. Medial angulation of styloid process on both sides was correlated with each other using rank correlation coefficient. Wilcoxon Signed Rank test was applied to test significant difference between pre-operative and post-operative symptoms scores.Result Significant positive correlation was found between the medial angulation of styloid process on right side and left side (? =0.81, p<0.001). Significant difference was also observed between pre and post-operative symptoms scores (z=-5.16, p<0.001) .Conclusion Possibility of Eagle’s syndrome should always be considered while examining patients with vague neck pain. 3D CT reconstruction is a gold standard investigation which helps in studying the relation of styloid process with surrounding structures along with accurate measurement of its length and medial angulation.Kathmandu Univ Med J 2013; 11(4): 305-309

Accelerating compute intensive medical imaging segmentation algorithms using hybrid CPU-GPU implementations

2016 ◽  
Vol 76 (3) ◽  
pp. 3537-3555 ◽  
Author(s):  
Mohammad A. Alsmirat ◽  
Yaser Jararweh ◽  
Mahmoud Al-Ayyoub ◽  
Mohammed A. Shehab ◽  
Brij B. Gupta
Keyword(s):  
Medical Imaging ◽  
Segmentation Algorithms

Integration of 3D Volumetric Computed Tomography Scan Image Data with Conventional Well Logs for Detection of Petrophysical Rock Classes

2021 ◽  
pp. 1-18
Author(s):  
Andres Gonzalez ◽  
Zoya Heidari ◽  
Olivier Lopez
Keyword(s):  
Ct Scan ◽  
Well Logs ◽  
Well Log ◽  
3D Ct ◽  
Rock Classification ◽  
Formation Evaluation ◽  
Rock Fabric ◽  
3D Ct Scan ◽  
Scan Data ◽  
Image Analysis Techniques

Summary Core measurements are used for rock classification and improved formation evaluation in both cored and noncored wells. However, the acquisition of such measurements is time-consuming, delaying rock classification efforts for weeks or months after core retrieval. On the other hand, well-log-based rock classification fails to account for rapid spatial variation of rock fabric encountered in heterogeneous and anisotropic formations due to the vertical resolution of conventional well logs. Interpretation of computed tomography (CT) scan data has been identified as an attractive and high-resolution alternative for enhancing rock texture detection, classification, and formation evaluation. Acquisition of CT scan data is accomplished shortly after core retrieval, providing high-resolution data for use in petrophysical workflows in relatively short periods of time. Typically, CT scan data are used as two-dimensional (2D) cross-sectional images, which is not suitable for quantification of three-dimensional (3D) rock fabric variation, which can increase the uncertainty in rock classification using image-based rock-fabric-related features. The methods documented in this paper aim to quantify rock-fabric-related features from whole-core 3D CT scan image stacks and slabbed whole-core photos using image analysis techniques. These quantitative features are integrated with conventional well logs and routine core analysis (RCA) data for fast and accurate detection of petrophysical rock classes. The detected rock classes are then used for improved formation evaluation. To achieve the objectives, we conducted a conventional formation evaluation. Then, we developed a workflow for preprocessing of whole-core 3D CT-scan image stacks and slabbed whole-core photos. Subsequently, we used image analysis techniques and tailor-made algorithms for the extraction of image-based rock-fabric-related features. Then, we used the image-based rock-fabric-related features for image-based rock classification. We used the detected rock classes for the development of class-based rock physics models to improve permeability estimates. Finally, we compared the detected image-based rock classes against other rock classification techniques and against image-based rock classes derived using 2D CT scan images. We applied the proposed workflow to a data set from a siliciclastic sequence with rapid spatial variations in rock fabric and pore structure. We compared the results against expert-derived lithofacies, conventional rock classification techniques, and rock classes derived using 2D CT scan images. The use of whole-core 3D CT scan image-stacks-based rock-fabric-related features accurately captured changes in the rock properties within the evaluated depth interval. Image-based rock classes derived by integration of whole-core 3D CT scan image-stacks-based and slabbed whole-core photos-based rock-fabric-related features agreed with expert-derived lithofacies. Furthermore, the use of the image-based rock classes in the formation evaluation of the evaluated depth intervals improved estimates of petrophysical properties such as permeability compared to conventional formation-based permeability estimates. A unique contribution of the proposed workflow compared to the previously documented rock classification methods is the derivation of quantitative features from whole-core 3D CT scan image stacks, which are conventionally used qualitatively. Furthermore, image-based rock-fabric-related features extracted from whole-core 3D CT scan image stacks can be used as a tool for quick assessment of recovered whole core for tasks such as locating best zones for extraction of core plugs for core analysis and flagging depth intervals showing abnormal well-log responses.

scholarly journals Morphometric Study on Mastoid Process for Determination of Sex by Using 3D CT Scan

2020 ◽  
Vol 9 (1) ◽  
pp. 85-89
Author(s):  
MY Dofe ◽  
◽  
KS Nemade ◽  
NY kamadi ◽  
◽  
...  
Keyword(s):  
Ct Scan ◽  
Mastoid Process ◽  
Morphometric Study ◽  
3D Ct ◽  
3D Ct Scan

How much is the effective dose from medical imaging in pediatric patients in the neurosurgery department?

2021 ◽  
Author(s):  
B. Zeinali-Rafsanjani ◽  
S. Haseli ◽  
R. Jalli ◽  
M. Saeedi-Moghadam
Keyword(s):  
Medical Imaging ◽  
Ionizing Radiation ◽  
Ct Scan ◽  
Effective Dose ◽  
Pediatric Patients ◽  
Ct Scans ◽  
Imaging Data ◽  
Plain Radiographs ◽  
Brain Ct ◽  
Abdomen Ct

Medical imaging with ionizing radiation in pediatric patients is rising, and their radiation sensitivity is 2–3 times more than adults. The objective of this study was to estimate the total effective dose (ED) of all medical imaging by CT scan and plain radiography in patients in pediatric neurosurgery department. Patients with at least one brain CT scan and recorded dose length product (DLP) were included. Patients’ imaging data were collected from the picture-archiving-and-communicating system (PACS) using their national code to find all their medical imaging. Total ED (mSv) from CT scans and plain radiographs were calculated. A total of 300 patients were included, of which 129 were females and 171 males with a mean age of 5.45 ± 4.34 years. Mean DLPs of brain, abdomen, and chest CT were 329.16, 393.06, 284.46 mGy.cm. The most frequent CT scans in these children were brain CT scans with ED range of 0.09 to 47.09 mSv. Total ED due to all CT scans and plain radiographs were in the range of 0.38 to 63.41 mSv. Although the mean DLP of each brain, chest, and abdomen CT of patients was in the range of DRLs reported by previous studies, the patients with numerous CT scans received more radiation doses than mean ED (6.21 mSv between all age groups). The most frequent CT scan was the brain, and the most frequent plain radiographs were chest and lower extremities. It can be concluded that reducing the number of CT scans or plain radiographs by appropriate physical exams or replacing them with modalities that do not use ionizing radiation can reduce ED.

Simulating blood rheology across scales: A hybrid LB-particle approach

2019 ◽  
Vol 30 (10) ◽  
pp. 1941003 ◽  
Author(s):  
Giacomo Falcucci ◽  
Marco Lauricella ◽  
Paolo Decuzzi ◽  
Simone Melchionna ◽  
Sauro Succi
Keyword(s):  
Lattice Boltzmann ◽  
Blood Cells ◽  
Hybrid Approach ◽  
Computational Cost ◽  
Blood Rheology ◽  
Numerical Approach ◽  
Particle Dynamics ◽  
Particle Methods ◽  
Blood Transport ◽  
Particle Approach

In this paper, we deploy the hybrid Lattice Boltzmann - Particle Dynamics (LBPD) method to investigate the transport properties of blood flow within arterioles and venules. The numerical approach is applied to study the transport of Red Blood Cells (RBC) through plasma, highlighting significant agreement with the experimental data in the seminal work by Fåhræus and Lindqvist. Moreover, the results provide evidence of an interesting hand-shaking between the range of validity of the proposed hybrid approach and the domain of viability of particle methods. A joint inspection of accuracy and computational cost, indicate that LBPD offers an appealing multiscale strategy for the study of blood transport across scales of motion, from macroscopic vessels, down to arterioles and venules, where particle methods can eventually take over.

scholarly journals 330 A hybrid model for genomic selection using prioritized SNPs based on FST scores in the presence of non-genotyped animals

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 51-51
Author(s):  
Sajjad Toghiani ◽  
Ling-Yun Chang ◽  
El H Hay ◽  
Andrew J Roberts ◽  
Samuel E Aggrey ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Hybrid Approach ◽  
Computational Cost ◽  
Simulated Data ◽  
Snp Markers ◽  
Genomic Relationship Matrix ◽  
Polygenic Effect ◽  
Relationship Matrix ◽  
Continuous Increase ◽  
Missing Genotypes

Abstract The dramatic advancement in genotyping technology has greatly reduced the complexity and cost of genotyping. The continuous increase in the density of marker panels is resulting in little to no improvement in the accuracy of genomic selection. Direct inversion of the genomic relationship matrix is infeasible for some livestock populations due to the excessive computational cost. In addition, most animals in genetic evaluation programs are non-genotyped. Including these animals in a genomic evaluation requires the imputation of the missing genotypes when using regression methods. To overcome these challenges, a hybrid approach is proposed. This approach fits a subset of SNP markers selected based on FST scores and a classical polygenic effect. The method was first tested using only genotyped animals and then extended to accommodate non-genotyped animals. The proposed approach was evaluated using simulated data for a trait with heritability of 0.1 and 0.4 and weaning weight in a crossbred beef cattle population. When all animals were genotyped, the hybrid approach using only 2.5% of prioritized SNPs exceeded the prediction accuracies of BayesB, BayesC, and GBLUP by more than 7%. When non-genotyped animals were incorporated, the proposed approach significantly outperformed ss-GBLUP method in terms of prediction accuracy under both simulated heritability scenarios. Although the results seem to depend on the genetic complexity of the trait, the proposed approach resulted in higher prediction accuracies than current methods. Furthermore, its computational costs in terms of CPU time and peak memory are substantially lower than the current methods.

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