Discriminant snakes for 3D reconstruction in medical images

2002 ◽  
Author(s):  
X.M. Pardo ◽  
P. Radeva
Keyword(s):  
3D Reconstruction ◽  
Medical Images

scholarly journals Nextmed: Automatic Imaging Segmentation, 3D Reconstruction, and 3D Model Visualization Platform Using Augmented and Virtual Reality

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2962 ◽  
Author(s):  
Santiago González Izard ◽  
Ramiro Sánchez Torres ◽  
Óscar Alonso Plaza ◽  
Juan Antonio Juanes Méndez ◽  
Francisco José García-Peñalvo
Keyword(s):  
Virtual Reality ◽  
3D Reconstruction ◽  
Medical Image ◽  
New Technologies ◽  
Medical Images ◽  
3D Visualization ◽  
Automatic Segmentation ◽  
Individual Case ◽  
Medical Professionals ◽  
Anatomical Structures

The visualization of medical images with advanced techniques, such as augmented reality and virtual reality, represent a breakthrough for medical professionals. In contrast to more traditional visualization tools lacking 3D capabilities, these systems use the three available dimensions. To visualize medical images in 3D, the anatomical areas of interest must be segmented. Currently, manual segmentation, which is the most commonly used technique, and semi-automatic approaches can be time consuming because a doctor is required, making segmentation for each individual case unfeasible. Using new technologies, such as computer vision and artificial intelligence for segmentation algorithms and augmented and virtual reality for visualization techniques implementation, we designed a complete platform to solve this problem and allow medical professionals to work more frequently with anatomical 3D models obtained from medical imaging. As a result, the Nextmed project, due to the different implemented software applications, permits the importation of digital imaging and communication on medicine (dicom) images on a secure cloud platform and the automatic segmentation of certain anatomical structures with new algorithms that improve upon the current research results. A 3D mesh of the segmented structure is then automatically generated that can be printed in 3D or visualized using both augmented and virtual reality, with the designed software systems. The Nextmed project is unique, as it covers the whole process from uploading dicom images to automatic segmentation, 3D reconstruction, 3D visualization, and manipulation using augmented and virtual reality. There are many researches about application of augmented and virtual reality for medical image 3D visualization; however, they are not automated platforms. Although some other anatomical structures can be studied, we focused on one case: a lung study. Analyzing the application of the platform to more than 1000 dicom images and studying the results with medical specialists, we concluded that the installation of this system in hospitals would provide a considerable improvement as a tool for medical image visualization.

An Improved Three-Dimensional Target Octonion Representation

2012 ◽  
Vol 263-266 ◽  
pp. 1614-1618
Author(s):  
Xiang Hua Chen ◽  
Juan Zhou
Keyword(s):  
3D Reconstruction ◽  
Traditional Method ◽  
Medical Images ◽  
Three Dimensional ◽  
Experimental Results ◽  
Three Dimensional Objects ◽  
Traditional Structure ◽  
Large Memory ◽  
Octree Representation

It is an efficient way to represent three-dimensional objects by octree.The traditional structure of pointer -based octree representation has several shortcomings,such as requiring large memory,missing relationship between two nodes,etc.Based on analyzing the space Iayout and the configuration of octree,this paper presents an improved octree for 3D representation.From the experimental results for 3D reconstruction of medical images,we can see the proposed method is superior to the traditional method in terms of the storing structure and visiting way,etc.

scholarly journals IBK – A NEW TOOL FOR MEDICAL IMAGE PROCESSING

2010 ◽  
Vol 13 (4) ◽  
pp. 20-27
Author(s):  
Linh Duy Tran ◽  
Linh Quang Huynh
Keyword(s):  
Image Processing ◽  
Diagnostic Imaging ◽  
3D Reconstruction ◽  
Programming Language ◽  
Medical Image ◽  
Medical Images ◽  
Rapid Development ◽  
Medical Image Processing ◽  
Matlab Programming

Along with the rapid development of diagnostic imaging equipment, software for medical image processing has played an important role in helping doctors and clinicians to reach accurate diagnoses. In this paper, methods to build a multipurpose tool based on Matlab programming language and its applications are presented. This new tool features enhancement, segmentation, registration and 3D reconstruction for medical images obtained from commonly used diagnostic imaging equipment.

scholarly journals AUTOMATIC ACTIVE CONTOURS PROPAGATION IN A SEQUENCE OF MEDICAL IMAGES

2006 ◽  
Vol 06 (02) ◽  
pp. 267-292 ◽  
Author(s):  
KHALIFA DJEMAL ◽  
WILLIAM PUECH ◽  
BRUNO ROSSETTO
Keyword(s):  
3D Reconstruction ◽  
Active Contours ◽  
Medical Images ◽  
Region Of Interest ◽  
Image Model ◽  
Dynamic Prediction ◽  
External Contour ◽  
Definition Of ◽  
Objects Localization ◽  
Prediction Of Displacements

In this paper we present a new algorithm to track an organ in a sequence of medical images in order to achieve a 3D reconstruction. The automatic method that we propose allows the tracking of the external contour of the anatomical organ in all the sequence from one contour initialized by the user on the first image. The required operations for our tracking method are the region-based active contours segmentation. The objects localization with dynamic prediction of displacements is based on the level-set functions and the definition of the region of interest for the robust local estimation of the image model. An application of this method is the 3D reconstruction of abdominal aorta.

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