A new model-based framework for lung tissue segmentation in three-dimensional thoracic CT images

2017 ◽  
Vol 12 (2) ◽  
pp. 339-346 ◽  
Author(s):  
Zeinab Naseri Samaghcheh ◽  
Fatemeh Abdoli ◽  
Hamid Abrishami Moghaddam ◽  
Mohammadreza Modaresi ◽  
Neda Pak
Keyword(s):  
Lung Tissue ◽  
Three Dimensional ◽  
Ct Images ◽  
Tissue Segmentation ◽  
New Model ◽  
Model Based ◽  
Thoracic Ct

Preoperative surgical simulation of laparoscopic adrenalectomy for neuroblastoma using a three-dimensional printed model based on preoperative CT images

2015 ◽  
Vol 50 (12) ◽  
pp. 2112-2115 ◽  
Author(s):  
Ryota Souzaki ◽  
Yoshiaki Kinoshita ◽  
Satoshi Ieiri ◽  
Naonori Kawakubo ◽  
Satoshi Obata ◽  
...  
Keyword(s):  
Laparoscopic Adrenalectomy ◽  
Surgical Simulation ◽  
Three Dimensional ◽  
Ct Images ◽  
Model Based ◽  
Preoperative Ct

Computer-aided classification of benign and malignant pulmonary nodules in three-dimensional thoracic CT images based on a hybrid classifier

2001 ◽  
Vol 1230 ◽  
pp. 1297-1298
Author(s):  
Y. Kawata ◽  
N. Niki ◽  
H. Ohmatsu ◽  
M. Kusumoto ◽  
R. Kakinuma ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Pulmonary Nodules ◽  
Ct Images ◽  
Hybrid Classifier ◽  
Thoracic Ct ◽  
Computer Aided

Three-dimensional liver model based on preoperative CT images as a tool to assist in surgical planning for hepatoblastoma in a child

2015 ◽  
Vol 31 (6) ◽  
pp. 593-596 ◽  
Author(s):  
Ryota Souzaki ◽  
Yoshiaki Kinoshita ◽  
Satoshi Ieiri ◽  
Makoto Hayashida ◽  
Yuhki Koga ◽  
...  
Keyword(s):  
Surgical Planning ◽  
Three Dimensional ◽  
Ct Images ◽  
Model Based ◽  
Liver Model ◽  
Preoperative Ct

scholarly journals Posture Estimation of a Human Body from Thermal Images of 2D Appearance Models of 3D Ellipsoidal Model

2009 ◽  
Vol 13 (3) ◽  
pp. 172-177 ◽  
Author(s):  
Mitsuhiro Hayase ◽  
◽  
Susumu Shimada ◽  
Keyword(s):  
Human Body ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Recognition Method ◽  
Thermal Images ◽  
New Model ◽  
Model Based ◽  
Ellipsoidal Model ◽  
Posture Estimation ◽  
Appearance Models

We propose a new model-based recognition method that involves the use of three-dimensional (3D) ellipsoidal models in various sizes and proportions as well as their two-dimensional (2D) appearance models. Most model-based vision is intended to recognize specified objects, and the model is specific to the object. However, our method can recognize various proportions of objects and was applied in posture estimation of the human body from thermal images.

A Study of Multilevel Banded Graph Cuts for Three-Dimensional Colon Tissue Segmentation

2017 ◽  
Vol 31 (09) ◽  
pp. 1755012 ◽  
Author(s):  
Wei He ◽  
Liyuan Zhang ◽  
Huamin Yang ◽  
Zhengang Jiang ◽  
Huimao Zhang ◽  
...  
Keyword(s):  
Time Complexity ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Graph Cuts ◽  
Ct Images ◽  
High Dimensional ◽  
Tissue Segmentation ◽  
Spatial Characteristics ◽  
Dimensional Image ◽  
Segmentation Accuracy

Graph cuts is an image segmentation method by which the region and boundary information of objects can be revolved comprehensively. Because of the complex spatial characteristics of high-dimensional images, time complexity and segmentation accuracy of graph cuts methods for high-dimensional images need to be improved. This paper proposes a new three-dimensional multilevel banded graph cuts model to increase its accuracy and reduce its complexity. Firstly, three-dimensional image is viewed as a high-dimensional space to construct three-dimensional network graphs. A pyramid image sequence is created by Gaussian pyramid downsampling procedure. Then, a new energy function is built according to the spatial characteristics of the three-dimensional image, in which the adjacent points are expressed by using a 26-connected system. At last, the banded graph is constructed on a narrow band around the object/background. The graph cuts method is performed on the banded graph layer by layer to obtain the object region sequentially. In order to verify the proposed method, we have performed an experiment on a set of three-dimensional colon CT images, and compared the results with local region active contour and Chan–Vese model. The experimental results demonstrate that the proposed method can segment colon tissues from three-dimensional abdominal CT images accurately. The segmentation accuracy can be increased to 95.1% and the time complexity is reduced by about 30% of the other two methods.

Preliminary study of visualizing membrane structures of spiculated pulmonary nodules in three-dimensional thoracic CT images

2016 ◽  
Author(s):  
Y. Kawata ◽  
N. Niki ◽  
H. Ohmatsu ◽  
K. Aokage ◽  
M. Kusumoto ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Pulmonary Nodules ◽  
Ct Images ◽  
Membrane Structures ◽  
Thoracic Ct ◽  
Preliminary Study

Automated extraction of pleural effusion in three-dimensional thoracic CT images

2009 ◽  
Author(s):  
Shoji Kido ◽  
Akinori Tsunomori
Keyword(s):  
Pleural Effusion ◽  
Three Dimensional ◽  
Ct Images ◽  
Automated Extraction ◽  
Thoracic Ct
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