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LOGISMOS—Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces: Cartilage Segmentation in the Knee Joint
2010
IEEE Transactions on Medical Imaging
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A novel method for simultaneous segmentation of multiple interacting surfaces belonging to multiple interacting objects, called LOGISMOS (layered optimal graph image segmentation of multiple objects and ...
Although trained on only a relatively small number of nine example images, this system achieved good performance. ...
Acknowledgments The contributions of C. Van Hofwegen, N. Laird, and N. Muhlenbruch who provided initial knee joint manual tracings, are gratefully acknowledged. ...
doi:10.1109/tmi.2010.2058861
pmid:20643602
pmcid:PMC3131162
fatcat:hnwxif523fcldeayigglefjuwu
Computer-Assisted Analysis of Biomedical Images
[article]
2021
arXiv
pre-print
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In this regard, frameworks based on advanced Machine Learning and Computational Intelligence can significantly improve traditional Image Processing and Pattern Recognition approaches. ...
Therefore, the computational analysis of medical and biological images plays a key role in radiology and laboratory applications. ...
Brain tumor segmentation based on a CA model This section presents a novel semi-automatic MR brain tumor image segmentation approach (GTVCUT) based on a CA model. ...
arXiv:2106.04381v1
fatcat:osqiyd3sbja3zgrby7bf4eljfm
Skull-stripping with machine learning deformable organisms
2014
Journal of Neuroscience Methods
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Our method borrows ideas from artificial life to govern a set of deformable models. ...
We tested our method on 838 T1-weighted images, evaluating results using distance and overlap error metrics based on expert gold standard segmentations. ...
Additional support was from the UCLA I2-IDRE Research Informatics and Computational Data Development Grant to PT and GP. ...
doi:10.1016/j.jneumeth.2014.07.023
pmid:25124851
pmcid:PMC4169789
fatcat:52jr4sxp7na2hflws4xhoxgcz4
External Force for Deformable Models in Medical Image Segmentation: A Survey
2011
Signal & Image Processing An International Journal
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The main purpose of survey is to identify and discuss each category with its principle, mathematical model, advantages, disadvantages and applications to medical image analysis. ...
These models also support highly intuitive interaction mechanisms, which helps medical practitioners to bring their expertise to bear on the model-based image interpretation task. ...
Suhuai Luo et al [27] proposed a new method to segment a tumour in brain MR images. Method is based on combining of balloon force and GVF models. ...
doi:10.5121/sipij.2011.2208
fatcat:nivreffym5hplfptkdi57tbyfa
Analysis of macular OCT images using deformable registration
2014
Biomedical Optics Express
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Examples of these applications are provided to demonstrate the potential benefits such techniques can have on our understanding of retinal disease. ...
The approach begins with an initial translation to align the fovea of each subject, followed by a linear rescaling to align the top and bottom retinal boundaries. ...
Acknowledgments This work was supported by the NIH/NEI under grant R21-EY022150, NIH/NINDS R01-NS082347 and the Intramural Research Program of NINDS. ...
doi:10.1364/boe.5.002196
pmid:25071959
pmcid:PMC4102359
fatcat:j3wjamhx4zgdvdyfylvvwi7ys4
Multimodal characterization of the human nucleus accumbens
2019
NeuroImage
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this region. ...
These observations motivate a segmentation of the NAc into subregions, which we produce from a diffusion-tractography based analysis of 245 young, unrelated healthy subjects. ...
The base of the model was set to zero potential to represent distant current return to the IPG in the chest, the internal boundaries within the model were set to continuity, and the outer boundary was ...
doi:10.1016/j.neuroimage.2019.05.019
pmid:31077843
pmcid:PMC7341972
fatcat:o73orjsdm5cmldlejnzd6hl3za
High-Resolution Fiber Tract Reconstruction in the Human Brain by Means of Three-Dimensional Polarized Light Imaging
2011
Frontiers in Neuroinformatics
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To exemplarily highlight the potential of this approach, fiber orientation maps and 3D fiber models were reconstructed in selected regions of the brain (e.g., Corpus callosum, Internal capsule, Pons). ...
It is based on the birefringence of the myelin sheaths surrounding axons, and enables the high-resolution analysis of myelinated axons constituting the fiber tracts. 3D-PLI provides the mapping of spatial ...
Our work was partly supported by the Initiative and Network Fund of the Helmholtz Association within the Helmholtz Alliance on Systems Biology ("Human Brain Model"). ...
doi:10.3389/fninf.2011.00034
pmid:22232597
pmcid:PMC3248698
fatcat:ilxr5uofsvgcnllhus3gzjlepq
Medical Imaging Synthesis using Deep Learning and its Clinical Applications: A Review
[article]
2020
arXiv
pre-print
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performances with related clinical applications on representative studies. ...
This paper reviewed the deep learning-based studies for medical imaging synthesis and its clinical application. ...
The 377 synthetic MR image sets with tumor labels were then incorporated into segmentation model training. ...
arXiv:2004.10322v1
fatcat:bkhct7wzjnfrrd4kwa4rqw6rbe
Image Segmentation with a Unified Graphical Model
2010
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Experimental results on the Weizmann horse data set, on the VOC2006 cow data set, and on the MSRC2 multiclass data set demonstrate that our approach achieves favorable results compared to state-of-the-art ...
Specifically, we first propose to employ Conditional Random Field (CRF) to model the spatial relationships among image superpixel regions and their measurements. ...
The authors also want to thank the anonymous reviewers and the editors who gave them valuable comments on this work. ...
doi:10.1109/tpami.2009.145
pmid:20558874
fatcat:d3v5j5h3zzbk7eusno2xpa4gri
Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI
[article]
2019
arXiv
pre-print
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Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multi-sequence 3D imaging. ...
This study demonstrates automated detection and segmentation of brain metastases on multi-sequence MRI using a deep learning approach based on a fully convolution neural network (CNN). ...
Işın A, Direkoğlu C, Şah M: Review of MRI-based Brain double dose contrast-enhanced magnetic resonance
Tumor Image Segmentation Using Deep Learning imaging for clear delineation of gross ...
arXiv:1903.07988v1
fatcat:igpmay2pzve3do4ctt26sn3ys4
Improving MR brain image segmentation using self-organising maps and entropy-gradient clustering
2014
Information Sciences
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The primary brain image segmentation goal is to partition a given brain image into different regions representing anatomical structures. ...
Magnetic resonance image (MRI) segmentation is especially interesting because the accurate representation of white matter, grey matter and cerebrospinal fluid provides a way to identify many brain disorders ...
Similar to the way that a human expert has to learn to recognise different regions on the MR image, segmentation algorithms are based on prior knowledge. ...
doi:10.1016/j.ins.2013.10.002
fatcat:4sgzyuipubfztd3mjzakubgylu
Automatic MRI Database Exploration and Applications
1997
International journal of pattern recognition and artificial intelligence
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We present as examples of applications the building of an average volume of interest and preliminary results of classi cation according to morphology. keywords image database, exploration, volume of interest ...
The design of representative models of the human body is of great interest to medical doctors. ...
On light of those results, comparisons bases on mutual information techniques are expected to give good classi cations. ...
doi:10.1142/s0218001497000627
fatcat:gdn22nx5lffrxmbnmbq53osua4
Hippocampal gray matter reduction associates with memory deficits in adolescents with history of prematurity
2004
NeuroImage
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Using optimized voxel-based morphometry (VBM), we compared the relationship between hippocampal and thalamic gray matter loss and memory impairment in 22 adolescents with history of prematurity (HP) and ...
Using stereological methods, we also observed a reduction in hippocampal volume, with left posterior predominance. ...
Caldú , a research grant from the University of Barcelona to A. Narberhaus, and the grant AP2002-0737 (Ministerio de Educación, Cultura y Deporte) to M. ...
doi:10.1016/j.neuroimage.2004.07.029
pmid:15528087
fatcat:aw5r2uue2jaxbnevu5c6qo5gjm
Modeling & Analysis
2003
NeuroImage
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Thus, it was inclusive than exclusively fully on "double-blind, placebo-controlled" experiments. ...
Most of the automatic brain image segmentation algorithms are using the MNI templates, which have been generated from MR images of young healthy individuals (mean age 23.4+-4.1 years). ...
Conclusion We propose a processing chain to analyse structural brain changes in time series of MR images. ...
doi:10.1016/s1053-8119(05)70006-9
fatcat:zff2suxcofbxvetfrwfwcxi3zm
Intersection Based Motion Correction of Multislice MRI for 3-D in Utero Fetal Brain Image Formation
2010
IEEE Transactions on Medical Imaging
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The method is tested on simulated data with known motions and is applied to retrospectively reconstruct 3-D images from a range of clinically acquired imaging studies. ...
In recent years, postprocessing of fast multislice magnetic resonance imaging (MRI) to correct fetal motion has provided the first true 3-D MR images of the developing human brain in utero. ...
ACKNOWLEDGMENT The authors would also like to thank Dr. R. Henry for advice on the imaging protocols and assistance with the transfer of imaging data. ...
doi:10.1109/tmi.2009.2030679
pmid:19744911
pmcid:PMC3328314
fatcat:3q6ynjl5kvhlfc2656ofsa2qmu
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