Bayesian segmentation of human facial tissue using 3D MR-CT information fusion, resolution enhancement and partial volume modelling

2016-02-01
Şener, Emre
Mumcuoğlu, Ünal Erkan
Hamcan, Salih
Background: Accurate segmentation of human head on medical images is an important process in a wide array of applications such as diagnosis, facial surgery planning, prosthesis design, and forensic identification.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Suggestions

Automatic Bayesian segmentation of human facial tissue using 3D MR-CT fusion by incorporating models of measurement blurring, noise and partial volume
Şener, Emre; Kanoğlu, Utku; Mumcuoğlu, Ünal Erkan; Department of Engineering Sciences (2012)
Segmentation of human head on medical images is an important process in a wide array of applications such as diagnosis, facial surgery planning, prosthesis design, and forensic identification. In this study, a new Bayesian method for segmentation of facial tissues is presented. Segmentation classes include muscle, bone, fat, air and skin. The method incorporates a model to account for image blurring during data acquisition, a prior helping to reduce noise as well as a partial volume model. Regularization ba...
Automatic segmentation of human facial tissue by MRI-CT fusion: A feasibility study
Kale, Emre H.; Mumcuoğlu, Ünal Erkan; HAMCAN, Salih (2012-12-01)
The aim of this study was to develop automatic image segmentation methods to segment human facial tissue which contains very thin anatomic structures. The segmentation output can be used to construct a more realistic human face model for a variety of purposes like surgery planning, patient specific prosthesis design and facial expression simulation. Segmentation methods developed were based on Bayesian and Level Set frameworks, which were applied on three image types: magnetic resonance imaging (MRI), compu...
Review of MRI-based Brain Tumor Image Segmentation Using Deep Learning Methods
Işın, Ali; Direkoğlu, Cem; Şah, Melike (Elsevier BV; 2016)
Brain tumor segmentation is an important task in medical image processing. Early diagnosis of brain tumors plays an important role in improving treatment possibilities and increases the survival rate of the patients. Manual segmentation of the brain tumors for cancer diagnosis, from large amount of MRI images generated in clinical routine, is a difficult and time consuming task. There is a need for automatic brain tumor image segmentation. The purpose of this paper is to provide a review of MRI-based brain ...
Image segmentation with Improved region modeling
Ersoy, Ozan; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2004)
Image segmentation is an important research area in digital image processing with several applications in vision-guided autonomous robotics, product quality inspection, medical diagnosis, the analysis of remotely sensed images, etc. The aim of image segmentation can be defined as partitioning an image into homogeneous regions in terms of the features of pixels extracted from the image. Image segmentation methods can be classified into four main categories: 1) clustering methods, 2) region-based methods, 3) ...
Evaluation of 3D printed carotid anatomical models in planning carotid artery stenting
Gocer, Hakan; Durukan, Ahmet Baris; Tunc, Osman; Naseri, Erdinc; Ercan, Ertugrul (Baycinar Tibbi Yayincilik, 2020-04-01)
Background: We aimed to investigate the potential role of three-dimensional printed anatomical models in pre-procedural planning, practice, and selection of carotid artery stent and embolic protection device size and location.
Citation Formats
E. Şener, Ü. E. Mumcuoğlu, and S. Hamcan, “Bayesian segmentation of human facial tissue using 3D MR-CT information fusion, resolution enhancement and partial volume modelling,” COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, pp. 31–44, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/30461.