Semiautomatic Segmentation of Plant Golgi Stacks in Electron Tomograms Using 3dmod

2017 ◽  
pp. 97-104 ◽  
Author(s):  
Keith Ka Ki Mai ◽  
Byung-Ho Kang
Keyword(s):  
Semiautomatic Segmentation

scholarly journals Semiautomatic Segmentation of Vertebrae in Lateral X-rays Using a Conditional Shape Model

2007 ◽  
Vol 14 (10) ◽  
pp. 1156-1165 ◽  
Author(s):  
J. Eugenio Iglesias ◽  
Marleen de Bruijne
Keyword(s):  
X Rays ◽  
Shape Model ◽  
Semiautomatic Segmentation

scholarly journals Computer-Assisted Segmentation of Videocapsule Images Using Alpha-Divergence-Based Active Contour in the Framework of Intestinal Pathologies Detection

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
L. Meziou ◽  
A. Histace ◽  
F. Precioso ◽  
O. Romain ◽  
X. Dray ◽  
...  
Keyword(s):  
Gastrointestinal Tract ◽  
Active Contour ◽  
Standard Technique ◽  
Poor Quality ◽  
Computer Assisted ◽  
Contour Segmentation ◽  
Semiautomatic Segmentation ◽  
Different Types ◽  
Statistical Similarity ◽  
Wireless Capsule

Visualization of the entire length of the gastrointestinal tract through natural orifices is a challenge for endoscopists. Videoendoscopy is currently the “gold standard” technique for diagnosis of different pathologies of the intestinal tract. Wireless capsule endoscopy (WCE) has been developed in the 1990s as an alternative to videoendoscopy to allow direct examination of the gastrointestinal tract without any need for sedation. Nevertheless, the systematic postexamination by the specialist of the 50,000 (for the small bowel) to 150,000 images (for the colon) of a complete acquisition using WCE remains time-consuming and challenging due to the poor quality of WCE images. In this paper, a semiautomatic segmentation for analysis of WCE images is proposed. Based on active contour segmentation, the proposed method introduces alpha-divergences, a flexible statistical similarity measure that gives a real flexibility to different types of gastrointestinal pathologies. Results of segmentation using the proposed approach are shown on different types of real-case examinations, from (multi)polyp(s) segmentation, to radiation enteritis delineation.

scholarly journals Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity

2020 ◽  
Vol 53 (2) ◽  
Author(s):  
F.C.F. Dionísio ◽  
L.S. Oliveira ◽  
M.A. Hernandes ◽  
E.E. Engel ◽  
R.M. Rangayyan ◽  
...  
Keyword(s):  
High Similarity ◽  
Semiautomatic Segmentation ◽  
Bone Sarcomas

scholarly journals The influence of craniofacial morphology on the upper airway dimensions

2014 ◽  
Vol 85 (5) ◽  
pp. 874-880 ◽  
Author(s):  
Iveta Indriksone ◽  
Gundega Jakobsone
Keyword(s):  
Linear Regression Analysis ◽  
Upper Airway ◽  
Correlation Coefficients ◽  
Craniofacial Morphology ◽  
Multivariate Linear Regression Analysis ◽  
Cross Sectional ◽  
Old Patients ◽  
Oropharyngeal Airway ◽  
Semiautomatic Segmentation ◽  
Airway Dimensions

ABSTRACT Objective:  To evaluate the influence of craniofacial morphology on the upper airway dimensions in healthy adult subjects. Materials and Methods:  The records of 276 healthy 17- to 27-year-old patients were extracted from the cone-beam computed tomography image database of the Institute of Stomatology, Riga Stradins University. Dolphin 11.7 software was used to evaluate craniofacial anatomy and semiautomatic segmentation of the upper airway. Measurements of oropharyngeal airway volume (OPV), minimal cross-sectional area (CSAmin), and nasopharyngeal airway volume (NPV) were obtained. The presence of adenoid tissues was recorded. Associations between variables were analyzed by Spearman's correlation coefficients, and multivariate linear regression analysis was used to identify factors that had a possible influence on upper airway dimensions. Results:  The following factors were identified as influencing the variability of NPV (23%): SNA angle, gender, and presence of adenoids. Statistically significant, although weak, correlations were found between SNB angle and OPV (r  =  0.144, P < .05) and CSAmin (r  =  0.182, P < .01). Conclusion:  The results suggest that craniofacial morphology alone does not have a significant influence on upper airway dimensions.

A semiautomatic segmentation method for interstitial needles in intraoperative 3D transvaginal ultrasound images for high-dose-rate gynecologic brachytherapy of vaginal tumors

Brachytherapy ◽  
2020 ◽  
Vol 19 (5) ◽  
pp. 659-668
Author(s):  
Jessica Robin Rodgers ◽  
William Thomas Hrinivich ◽  
Kathleen Surry ◽  
Vikram Velker ◽  
David D'Souza ◽  
...  
Keyword(s):  
Dose Rate ◽  
Transvaginal Ultrasound ◽  
High Dose Rate ◽  
High Dose ◽  
Ultrasound Images ◽  
Segmentation Method ◽  
Semiautomatic Segmentation

Volumetric Analysis of the Pterygopalatine Fossa by Semiautomatic Segmentation of Cone Beam Computed Tomography

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Max-Philipp Lentzen ◽  
Ali-Farid Safi ◽  
Maximilian Riekert ◽  
Veerle Visser-Vandewalle ◽  
Andrea Grandoch ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Volumetric Analysis ◽  
Pterygopalatine Fossa ◽  
Cone Beam ◽  
Semiautomatic Segmentation

A semiautomatic segmentation approach to corneal lesions

2020 ◽  
Vol 84 ◽  
pp. 106625
Author(s):  
Pablo V.C. Lima ◽  
Rodrigo de M.S. Veras ◽  
Luis H.S. Vogado ◽  
Helano M.B.F. Portela ◽  
João D.S. de Almeida ◽  
...  
Keyword(s):  
Semiautomatic Segmentation ◽  
Segmentation Approach

Semiautomatic segmentation of atherosclerotic carotid artery lumen using 3D ultrasound imaging

2013 ◽  
Author(s):  
Md. Murad Hossain ◽  
Khalid AlMuhanna ◽  
Limin Zhao ◽  
Brajesh Lal ◽  
Siddhartha Sikdar
Keyword(s):  
Carotid Artery ◽  
Ultrasound Imaging ◽  
3D Ultrasound ◽  
Semiautomatic Segmentation

scholarly journals Semiautomatic segmentation and follow-up of multicomponent low-grade tumors in longitudinal brain MRI studies

2014 ◽  
Vol 41 (5) ◽  
pp. 052303 ◽  
Author(s):  
Lior Weizman ◽  
Liat Ben Sira ◽  
Leo Joskowicz ◽  
Daniel L. Rubin ◽  
Kristen W. Yeom ◽  
...  
Keyword(s):  
Brain Mri ◽  
Low Grade ◽  
Semiautomatic Segmentation ◽  
Mri Studies
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