3D Visualization of Brain Tumors Using MR Images: A Survey

2019 ◽  
Vol 15 (4) ◽  
pp. 353-361 ◽  
Author(s):  
Dina Mohammed Sherif El-Torky ◽  
Maryam Nabil Al-Berry ◽  
Mohammed Abdel-Megeed Salem ◽  
Mohamed Ismail Roushdy
Keyword(s):  
Brain Tumors ◽  
3D Modeling ◽  
Brain Cancer ◽  
3D Visualization ◽  
Three Dimensional ◽  
Tumor Segmentation ◽  
Mr Images ◽  
The Public ◽  
Take The Best ◽  
Modeling Techniques

Background: Three-Dimensional visualization of brain tumors is very useful in both diagnosis and treatment stages of brain cancer. Discussion: It helps the oncologist/neurosurgeon to take the best decision in Radiotherapy and/or surgical resection techniques. 3D visualization involves two main steps; tumor segmentation and 3D modeling. Conclusion: In this article, we illustrate the most widely used segmentation and 3D modeling techniques for brain tumors visualization. We also survey the public databases available for evaluation of the mentioned techniques.

scholarly journals Usefulness of Three-dimensional MR Images of Brain Tumors for Surgical Simulation

2002 ◽  
Vol 58 (12) ◽  
pp. 1632-1638 ◽  
Author(s):  
KOUMEI NARITA ◽  
MUNEKI SASAKI ◽  
WATARU SAKURADA ◽  
HIDEMI SHIMIZU ◽  
HATSUO MIURA ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Surgical Simulation ◽  
Three Dimensional ◽  
Mr Images

scholarly journals A Three-Dimensional Reconstructive Study of Pelvic Cavity in the New Zealand Rabbit (Oryctolagus cuniculus)

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Sema Özkadif ◽  
Emrullah Eken ◽  
İbrahim Kalaycı
Keyword(s):  
New Zealand ◽  
3D Modeling ◽  
Three Dimensional ◽  
Pelvic Cavity ◽  
Zealand Rabbit ◽  
Pelvic Inclination ◽  
Modeling Techniques ◽  
Modeling Software ◽  
Shed Light ◽  
New Zealand Rabbits

The present study has been performed to reveal biometrical aspects and diameter-related differences in terms of sexes regarding pelvic cavity via three-dimensional (3D) reconstruction by using multidetector computed tomography (MDCT) images of pelvic cavity of the New Zealand rabbit. A total of 16 adult New Zealand rabbits, including 8 males and 8 females, were used in this study. Under anesthesia, the images obtained from MDCT were stacked and overlaid to reconstruct the 3D model of the pelvic cavity using 3D modeling software (Mimics 13.1). Measurements, such as the conjugate, transverse, and vertical diameters of the pelvic cavity, and the pelvic inclination were calculated and analyzed statistically. Biometrical differences of the pelvic diameters in New Zealand rabbits of both sexes were shown clearly. It was concluded that the pelvic diameters revealed by 3D modeling techniques can shed light on medical students who take both anatomy training and gynecological applications. The authors hope that the synchronization of medical approaches may give rise to novel diagnostic and therapeutic developments related to pelvic cavity.

Three- dimensional reconstruction of the thorax in the mongoose (Herpestes ichneumon)

2018 ◽  
Author(s):  
Sema Ozkadif ◽  
Ayse Haligur ◽  
Emrullah Eken
Keyword(s):  
3D Reconstruction ◽  
3D Modeling ◽  
Traffic Accidents ◽  
Three Dimensional ◽  
Thoracic Cavity ◽  
Wild Animals ◽  
Modeling Techniques ◽  
Dimensional Reconstruction ◽  
Modeling Software ◽  
Herpestes Ichneumon

Three- dimensional (3D) reconstruction obtained by using multidetector computed tomography (MDCT) images have widely been used in anatomical studies. Thorax is one of the most important body cavities necessary for the protection of lungs and heart in mammals. Two adult mongooses (1 male, 1 female) obtained from traffic accidents were used in this study. The images obtained from MDCT were stacked and 3D reconstruction of thorax was performed by overlaying images using a 3D modeling software (Mimics 13.1). Some measurements of thoracic cavity, lungs and sternum were taken from the reconstructive images of mongoose and indexes were calculated from these measurements. The morphometric parameters were recorded for both sexes. From the study, it could be concluded that the thoracic cavity, lungs and sternum imagings and findings revealed by 3D modeling techniques can be utilized for anatomical training of wild animals. This study is expected to help in the diagnosis and treatment of thorax diseases in wild animals.

scholarly journals Recognization and Systematization of MR Images using K Means Clustering and DNN

2020 ◽  
Vol 9 (6) ◽  
pp. 924-927
Keyword(s):  
Deep Learning ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Digital Health ◽  
High Accuracy ◽  
Tumor Segmentation ◽  
Mr Images ◽  
Brain Tumor Segmentation ◽  
Brain Tumor Diagnosis ◽  
The Brain

Brain tumors are the result of unusual growth and unrestrained cell disunity in the brain. Most of the medical image application lack in segmentation and labeling. Brain tumors can lead to loss of lives if they are not detected early and correctly. Recently, deep learning has been an important role in the field of digital health. One of its action is the reduction of manual decision in the diagnosis of diseases specifically brain tumor diagnosis needs high accuracy, where minute errors in judgment may lead to loss therefore, brain tumor segmentation is an necessary challenge in medical side. In recent time numerous ,methods exist for tumor segmentation with lack of accuracy. Deep learning is used to achieve the goal of brain tumor segmentation. In this work, three network of brain MR images segmentation is employed .A single network is compared to achieve segmentation of MR images using separate network .In this paper segmentation has improved and result is obtained with high accuracy and efficiency.

scholarly journals Interoperability of photogrammetry in 3D modeling: documentation, research and dissemination in the archaeological site of Jamila

2015 ◽  
Vol 6 (13) ◽  
pp. 51 ◽  
Author(s):  
Pedro R. Moya-Maleno ◽  
Juan Tormejón Valdelomar ◽  
David Vacas Madrid ◽  
Rocío Losa Sánchez
Keyword(s):  
3D Modeling ◽  
Three Dimensional ◽  
Archaeological Site ◽  
The Public ◽  
Ciudad Real ◽  
Archaeological Interpretation

This paper intends to be a sample, both theoretical and practical, of a protocol for the use of photogrammetric resources when generating a three-dimensional archaeological model. The use of said resources allows to cheaply compile, systematise, use and share the generated data –photogrammetric and 3D- in order to both work with hypothesis and share the knowledge –via online repositories with an academic public or with a wider audience using didactics and other means of spreading History and Archaeology–. As an example, the article analyses the possibilities and problems detected when applying said protocol at the site of the Columnated Building of Jamila (Villanueva de los Infantes, Ciudad Real, Spain). This archaeological site is ideal to put said protocol into practice, as one of its team’s aims is the public spreading of Archaeology of the site. Furthermore, it lacks information from its first archaeological seasons and a complex historical and archaeological interpretation, being a place with several reoccupations, some of them with unique typologies.

scholarly journals Segmentation of Brain Tumors Using Three-Dimensional Convolutional Neural Network on MRI Images 3D MedImg-CNN

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
High Performance ◽  
Three Dimensional ◽  
Tumor Segmentation ◽  
Dice Similarity Coefficient ◽  
Segmentation Method ◽  
Mr Images ◽  
Brain Tumor Segmentation ◽  
Fully Automatic

We consider the problem of fully automatic brain tumor segmentation in MR images containing glioblastomas. We propose a three Dimensional Convolutional Neural Network (3D MedImg-CNN) approach which achieves high performance while being extremely efficient, a balance that existing methods have struggled to achieve. Our 3D MedImg-CNN is formed directly on the raw image modalities and thus learn a characteristic representation directly from the data. We propose a new cascaded architecture with two pathways that each model normal details in tumors. Fully exploiting the convolutional nature of our model also allows us to segment a complete cerebral image in one minute. The performance of the proposed 3D MedImg-CNN with CNN segmentation method is computed using dice similarity coefficient (DSC). In experiments on the 2013, 2015 and 2017 BraTS challenges datasets; we unveil that our approach is among the most powerful methods in the literature, while also being very effective.

Ground Based 360° Three-Dimensional Display of the Computer Model

2013 ◽  
Vol 846-847 ◽  
pp. 1844-1847
Author(s):  
Shu Jun Xing ◽  
Xun Bo Yu ◽  
Tian Qi Zhao ◽  
Xin Zhu Sang ◽  
Yuan Fa Cai ◽  
...  
Keyword(s):  
Real World ◽  
3D Visualization ◽  
Three Dimensional ◽  
Experimental System ◽  
3D Display ◽  
The Real ◽  
The Public ◽  
Virtual Camera ◽  
Focus Plane ◽  
The Right

Most technologies provide three-dimensional (3D) display in the front of screens which are in parallel with the walls, and the sense of immersion is decreased. To get the right ground based 3D imaging, cameras imaging planes should be parallel to the public focus plane, and the cameras optical axes should be shifted to the center of the public focus plane in both vertical and horizontal directions. Virtual cameras are used to display 3D model in computer system. The virtual capturing methods for ground based 3D display are presented. The position of virtual camera is determined by the observers eye positions in the real world. An experimental system for ground based 360°3D display is demonstrated for viewing horizontally, which provides high-immersion 3D visualization. The displayed 3D scenes are compared with the real measurement in the real world.

scholarly journals Three Dimensional Field Recording in Archaeology: An Example from Gabii

2017 ◽  
Author(s):  
Rachel Opitz
Keyword(s):  
3D Modeling ◽  
3D Visualization ◽  
Three Dimensional ◽  
3D Image ◽  
Field Recording ◽  
The Future

“What is the future of 3D modeling in archaeology? At present, the 3D image is useful for illustrating artifacts and - in some cases - presenting archaeological and architectural relationships, but it has yet to prove itself as an essential basis for analysis or as a robust medium for communicating robust archaeological description. Will 3D visualization become more than just another method for providing illustrations for archaeological arguments?” This paper uses the experience of the Gabii Project to address these questions.

Procedural Modeling in 3D GIS Environment

2014 ◽  
Vol 3 (3) ◽  
pp. 17-34 ◽  
Author(s):  
Eva Tsiliakou ◽  
Tassos Labropoulos ◽  
Efi Dimopoulou
Keyword(s):  
3D Modeling ◽  
3D Visualization ◽  
Good Practice ◽  
Three Dimensional ◽  
3D Models ◽  
Three Dimensional Model ◽  
Rapid Urbanization ◽  
Procedural Modeling ◽  
Technological Advances ◽  
Third Dimension

3D space registration and visualization has become an imperative need in order to optimally reflect all complex cases of rapid urbanization of property rights and restrictions. Besides, current technological advances as well as the availability of sophisticated software packages (proprietary or open source) call for 3D modeling especially in the GIS domain. Within this context, GIS community's present demands concerning the third dimension are discussed, while a variety of 3D modeling techniques is presented, with special emphasis on procedural modeling. Procedural modeling refers to a variety of techniques for the algorithmic generation of detailed 3D models and composite facade textures from sets of rules which are called grammars. In this paper procedural modeling is employed via CityEngine software focusing on the 3D visualization of the National Technical University of Athens (NTUA) campus' three-dimensional model, rendering a higher detail on the School of Rural and Surveying Engineering (SRSE). This algorithmic modeling concept is based on the principle that all real world buildings are defined by rules, since repetitive patterns and hierarchical components describe their geometry. The detailed geometries of the model derived from the application of CGA (Computer Generated Architecture) shape grammars on selected footprints, and the process resulted in a final 3D model, optimally describing the built environment and proved to be a good practice example of 3D visualization.

Recent advancements in Fuzzy C-means based techniques for brain MRI Segmentation

2021 ◽  
Vol 16 ◽  
Author(s):  
Ghazanfar Latif ◽  
Jaafar Alghazo ◽  
Fadi N. Sibai ◽  
D.N.F. Awang Iskandar ◽  
Adil H. Khan
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Brain Mri ◽  
Tumor Segmentation ◽  
Brain Anatomy ◽  
Mri Segmentation ◽  
Brain Tumor Segmentation ◽  
Brain Images ◽  
Low Contrast ◽  
Fuzzy C Means

Background: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques. Objective: In this paper, a comprehensive review is presented on all thirteen variations of FCM segmentation techniques. In the review process, the concentration is on the use of FCM segmentation techniques for brain tumors. Brain tumor segmentation is a vital step in the process of automatically diagnosing brain tumors. Unlike segmentation of other types of images, brain tumor segmentation is a very challenging task due to the variations in brain anatomy. The low contrast of brain images further complicates this process. Early diagnosis of brain tumors is indeed beneficial to patients, doctors, and medical providers. Results: FCM segmentation works on images obtained from magnetic resonance imaging (MRI) scanners, requiring minor modifications to hospital operations to early diagnose tumors as most, if not all, hospitals rely on MRI machines for brain imaging. In this paper, we critically review and summarize FCM based techniques for brain MRI segmentation.

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