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Automatic Detection of Amyloid Beta Plaques in Somatosensory Cortex of an Alzheimer's Disease Mouse using Deep Learning

Heemoon Yoon, Mira Park, Soonja Yeom, Matthew T.K. Kirkcaldie, Peter Summons, Sang-Hee Lee
2021 IEEE Access  
This study contributes to image analysis in the field of neuroscience, allowing region-specific quantitation of image features using a deep learning approach.  ...  The framework has three phases: data acquisition to enhance image quality using preprocessing techniques and image normalization with a novel plaque removal algorithm, then an anatomical segmentation phase  ...  ACKNOWLEDGEMENTS Mouse brain sections and images were prepared by Ellie Bucher, supported by the Mason Foundation for Medical Research (project MAS2016F031), Australia.  ... 
doi:10.1109/access.2021.3132401 fatcat:oaozvu4z6bbhfgpeqdxluy533u

Novel MRI-derived quantitative biomarker for cardiac function applied to classifying ischemic cardiomyopathy within a Bayesian rule learning framework

Prahlad G. Menon, Lailonny Morris, Mara Staines, Joao Lima, Daniel C. Lee, Vanathi Gopalakrishnan, Sebastien Ourselin, Martin A. Styner
2014 Medical Imaging 2014: Image Processing  
RMS-P2PD, when contrasted against a collective normal reference, is a promising biomarker to investigate further in its utility for identifying quantitative signs of pathological endocardial function which  ...  The novel RMS-P2PD marker was tested as a cardiac function based feature for automatic patient classification using a Bayesian Rule Learning (BRL) framework.  ...  Using BRL, it was possible to quantitatively evidence the merit of the proposed novel RMS-P2PD biomarker for identifying quantitative signs of pathological endocardial function.  ... 
doi:10.1117/12.2042118 pmid:26005248 pmcid:PMC4440803 dblp:conf/miip/MenonMSL0G14 fatcat:caekyvl7obefvitzzbdpwxt3ke

Generative RGB-D Face Completion for Head-Mounted Display Removal

Nels Numan, Frank ter Haar, Pablo Cesar
2021 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)  
To address this, we proposed a framework that is capable of the virtual removal of head-mounted displays in RGB-D images, which is referred to as the task of HMD removal.  ...  Thus, RGB-D sensors are able to capture both the visual and geometric properties of a space, including any objects or people.  ...  Acknowledgements I would like to express my sincerest gratitude to the following people. • My supervisors, Frank ter Haar and Pablo Cesar, for providing invaluable guidance through their constructive feedback  ... 
doi:10.1109/vrw52623.2021.00028 fatcat:sbcco2znvnhvfpq3crk2xlqlza

A Variational Approach to Exploit Prior Information in Object-Background Segregation: Application to Retinal Images

Luca Bertelli, Jiyun Byun, B. S. Manjunath
2007 2007 IEEE International Conference on Image Processing  
In particular, we present an approach that exploits the knowledge about foreground and background information given in a reference image, in segmenting images containing similar objects or regions.  ...  One of the main challenges in image segmentation is to adapt prior knowledge about the objects/regions that are likely to be present in an image, in order to obtain more precise detection and recognition  ...  OBJECT/BACKGROUND SEGMENTATION USING DISSIMILARITIES WITH A REFERENCE Consider an image I 1 and a reference image I 2 .  ... 
doi:10.1109/icip.2007.4379521 dblp:conf/icip/BertelliBM07 fatcat:xeforgvkqrhwfouszo22ahexr4

Real-Time Quantitative Assessment of Accuracy and Precision of Blood Volume Derived from DCE-MRI in Individual Patients During a Clinical Trial

2019 Tomography  
We developed a framework for real-time quantitative assessment of QI metrics and evaluated accuracy and precision of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI)-derived blood volume  ...  Our framework of real-time quantitative assessment of QI metrics during a clinical trial can be translated to different QI metrics and organ-sites for supporting QI-based decision-making that warrants  ...  Disclosures: No disclosures to report. Conflict of Interest: The authors have no conflict of interest to declare.  ... 
doi:10.18383/j.tom.2018.00029 pmid:30854443 pmcid:PMC6403042 fatcat:5vdjinhdejfkxockklqmuvz6ky

An MRI derived articular cartilage visualization framework

S. Akhtar, C.L. Poh, R.I. Kitney
2007 Osteoarthritis and Cartilage  
Objective: We present a multi-dimensional framework for the visualization of femoral articular cartilage.  ...  Quantitative interaction with the 2D WearMap was assisted by the ability to ascertain cartilage surface dimensions and TrackBack from a point of interest to the original MR image.  ...  Acknowledgements The authors would like to thank Dr Rasu B. K. Shrestha (MD) for providing the MR images from patients with OA; Mr Tristan Lane for developing the segmentation process.  ... 
doi:10.1016/j.joca.2007.03.009 pmid:17707660 fatcat:ldpr67z5ofbjvouceefznbtarm

A non-parametric approach to automatic change detection in MRI images of the brain

Hae Jong Seo, Peyman Milanfar
2009 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
The method is based on the computation of a local kernel from the reference image, which measures the likeness of a pixel to its surroundings.  ...  We present a novel approach to change detection between two brain MRI scans (reference and target.)  ...  We refer the interested reader to [1] and references therein for a good summary.  ... 
doi:10.1109/isbi.2009.5193029 dblp:conf/isbi/SeoM09 fatcat:pmog6nfsunbgnlremgjhthgclm

Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step

Sylvia Rueda, Caroline L. Knight, Aris T. Papageorghiou, J. Alison Noble
2015 Medical Image Analysis  
To appreciate the accuracy and robustness of the methodology across clinical data of varying appearance and quality, a novel entropy-based quantitative image quality assessment of the different regions  ...  The new method is applied to 81 US images of the fetal arm acquired at multiple gestational ages, as a means to define a new automated image-based biomarker of fetal nutrition.  ...  Two normals on each side of each detected gap are then identified at a fixed distance D (Fig. 7(a) ).  ... 
doi:10.1016/j.media.2015.07.002 pmid:26319973 pmcid:PMC4686006 fatcat:56drs7snurdlromlxes6ydasva

Recovering depth of a dynamic scene using real world motion prior

Adarsh Kowdle, Noah Snavely, Tsuhan Chen
2012 2012 19th IEEE International Conference on Image Processing  
We can then incorporate this real world motion into the plane sweep stereo framework to obtain a more accurate depth for the dynamic object.  ...  Given a video of a dynamic scene captured using a dynamic camera, we present a method to recover a dense depth map of the scene with a focus on estimating the depth of the dynamic objects.  ...  We allow for the segmented dynamic object region in the reference frame to undergo an in-plane shift of a maximum of ∆d in either direction and evaluate the best score (NCC) for this region.  ... 
doi:10.1109/icip.2012.6467083 dblp:conf/icip/KowdleSC12 fatcat:ypz2hfrterhdtkpvvg5fyzou64

Target-dependent UNITER: A Transformer-Based Multimodal Language Comprehension Model for Domestic Service Robots [article]

Shintaro Ishikawa, Komei Sugiura
2021 arXiv   pre-print
We extend the UNITER approach by introducing a new architecture for handling the target candidates.  ...  In this paper, we propose Target-dependent UNITER, which learns the relationship between the target object and other objects directly by focusing on the relevant regions within an image, rather than the  ...  Multimodal language understanding for fetching instructions (MLU-FI) is similar to VRE in that the goal is to ground objects in the image with respect to a referring expression.  ... 
arXiv:2107.00811v1 fatcat:qhaxgjttsnhc3gnuahqdlh7hny

Object detection using optical and LiDAR data fusion

Onur Tasar, Selim Aksoy
2016 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)  
to obtain candidate image parts that contain different object classes, and incorporates spectral and height data with spatial information in a graph cut framework to segment the rest of the image where  ...  Fusion of aerial optical and LiDAR data has been a popular problem in remote sensing as they carry complementary information for object detection.  ...  We adapt the binary s-t cut framework described in [7] . In our formulation, each pixel in a mixed region corresponds to a node in the graph.  ... 
doi:10.1109/igarss.2016.7730879 dblp:conf/igarss/TasarA16 fatcat:xncsg3bsuvdonhedhwigqfinuq

A landmark-free framework for the detection and description of shape differences in embryos

S. M. Rolfe, L. G. Shapiro, T. C. Cox, A. M. Maga, L. L. Cox
2011 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
These methods are shown to detect regions of difference when evaluated on chick embryo images warped with small magnitude deformations in regions critical to midfacial development.  ...  This method uses deformable registration to produce a dense vector field describing the point correspondences between two images.  ...  Planned future work will extend this method towards the goal of developing a framework to produce quantitative characterizations of normal embryonic growth patterns.  ... 
doi:10.1109/iembs.2011.6091276 pmid:22255499 pmcid:PMC3261520 dblp:conf/embc/RolfeSCMC11 fatcat:vruswvnq4reudotwlgvkptgwti

Color Image Segmentation Metrics [article]

Majid Harouni, Hadi Yazdani Baghmaleki
2020 arXiv   pre-print
Furthermore, a conceptual comparison of these metrics is provided at a high level of abstraction and is discussed for understanding the quantitative changes in different image segmentation results.  ...  The decision-making process in selecting a suitable evaluation metric is still very serious because each metric tends to favor a different segmentation method for each benchmark dataset.  ...  common boundary pixels in both a machine-segmented object and its reference region are similar.  ... 
arXiv:2010.09907v1 fatcat:x4rxlck24jdvpg7rgbc3fvxqr4

An annotated test-retest collection of prostate multiparametric MRI

Andriy Fedorov, Michael Schwier, David Clunie, Christian Herz, Steve Pieper, Ron Kikinis, Clare Tempany, Fiona Fennessy
2018 Scientific Data  
Standard of care use of mpMRI in clinic relies on visual interpretation of the images by an expert. mpMRI is also increasingly used as a quantitative imaging biomarker of the disease.  ...  Here we present an mpMRI dataset consisting of baseline and repeat prostate MRI exams for 15 subjects, manually annotated to define regions corresponding to lesions and anatomical structures, and accompanied  ...  Acknowledgements This work was supported by the National Institutes of Health National Cancer Institute Informatics Technology for Cancer Research (ITCR) and Quantitative Imaging Network (QIN) initiatives  ... 
doi:10.1038/sdata.2018.281 fatcat:oip2lz47szbppfdb7ynxd6e5by

Domain-Generalized Textured Surface Anomaly Detection [article]

Shang-Fu Chen, Yu-Min Liu, Chia-Ching Lin, Trista Pei-Chun Chen, Yu-Chiang Frank Wang
2022 arXiv   pre-print
Anomaly detection aims to identify abnormal data that deviates from the normal ones, while typically requiring a sufficient amount of normal data to train the model for performing this task.  ...  it can also localize abnormal regions in the query image.  ...  Acknowledgement We thank National Center for Highperformance Computing (NCHC) and Inventec Cooperation for providing computational and storage resources.  ... 
arXiv:2203.12304v1 fatcat:4frrnh544rgwfeksotq3m7wlf4
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