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ECR 2011 Book of Abstracts - A - Postgraduate Educational Programme

2011 Insights into Imaging  
First angiograms with specific angulations are performed to identify the prostatic arteries. Deep knowledge of the pelvic arterial anatomy is essential because there are several variations.  ...  Using volumetric assessment, semi-automatic lesion segmentation and voxelwise analysis in heterogeneous tumours. 5.  ...  CT features of pulmonary arterial hypertension include dilatation of the main pulmonary artery, with a diameter greater than or equal to 29 mm, a ratio to the aortic diameter greater than 1:1 and a segmental  ... 
doi:10.1007/s13244-011-0078-3 pmid:23100070 pmcid:PMC3533621 fatcat:qa3ln4hhvve2hhumgwwnmykgoe

ECR 2016 Book of Abstracts - A - Postgraduate Educational Programme

2016 Insights into Imaging  
First angiograms with specific angulations are performed to identify the prostatic arteries. Deep knowledge of the pelvic arterial anatomy is essential because there are several variations.  ...  Using volumetric assessment, semi-automatic lesion segmentation and voxelwise analysis in heterogeneous tumours. 5.  ...  CT features of pulmonary arterial hypertension include dilatation of the main pulmonary artery, with a diameter greater than or equal to 29 mm, a ratio to the aortic diameter greater than 1:1 and a segmental  ... 
doi:10.1007/s13244-016-0474-9 pmid:26873353 pmcid:PMC4762839 fatcat:itxslbcacjhh3kixfkcwmdbt44

ECR 2013 Book of Abstracts - A - Postgraduate Educational Programme

2013 Insights into Imaging  
First angiograms with specific angulations are performed to identify the prostatic arteries. Deep knowledge of the pelvic arterial anatomy is essential because there are several variations.  ...  Using volumetric assessment, semi-automatic lesion segmentation and voxelwise analysis in heterogeneous tumours. 5.  ...  CT features of pulmonary arterial hypertension include dilatation of the main pulmonary artery, with a diameter greater than or equal to 29 mm, a ratio to the aortic diameter greater than 1:1 and a segmental  ... 
doi:10.1007/s13244-013-0227-y pmid:23468009 pmcid:PMC3666656 fatcat:yitsk227mba2pl7wcypouf6tz4

ECR 2015 Book of Abstracts - A - Postgraduate Educational Programme

2015 Insights into Imaging  
First angiograms with specific angulations are performed to identify the prostatic arteries. Deep knowledge of the pelvic arterial anatomy is essential because there are several variations.  ...  Using volumetric assessment, semi-automatic lesion segmentation and voxelwise analysis in heterogeneous tumours. 5.  ...  CT features of pulmonary arterial hypertension include dilatation of the main pulmonary artery, with a diameter greater than or equal to 29 mm, a ratio to the aortic diameter greater than 1:1 and a segmental  ... 
doi:10.1007/s13244-015-0386-0 pmid:25708993 pmcid:PMC4349897 fatcat:m7eyvqcwojfpvf3lr5hy6dwjb4

Semi-supervised and weakly-supervised learning with spatio-temporal priors in medical image segmentation

Gabriele Valvano
2021
With the advent of faster and higher-quality imaging technologies, the amount of data that is possible to collect for each patient is paving the way toward personalised medicine.  ...  In the thesis, we also open new avenues for future research using AI with limited annotations, which we believe is key to developing robust AI models for medical image analysis.  ...  Matthews, and Daniel Rueckert (2017). “Semi-supervised Learning For Network- Based Cardiac MR Image Segmentation”.  ... 
doi:10.13118/imtlucca/e-theses/344/ fatcat:qru63k6hibed3pwtxemhd523ua

SU-FF-I-79: Java-Based Plugin for Tomographic Reconstruction for SPECT Data

M Andrade, M Costa, A Marques da Silva
2006 Medical Physics (Lancaster)  
A 67.5mm × 162.5mm × 20.8mm region of interest surrounding the spinal cord was extracted for registration.  ...  Purpose: Digital tomosynthesis (DTS) is a method for reconstructing 3D images from cone-beam projection data acquired with limited angulation (e.g., 40 o ) of an x-ray source, and is much faster and lower  ...  Method and Materials: The highly accurate SST turbulence model is introduced in the simulation of blood flow in the severely constricted region at the ostium of a human renal artery, obtained from CT scans  ... 
doi:10.1118/1.2240759 fatcat:5we2nvgwx5hrxcv2ngufce6obq

Abstracts Presented at the Thirty–Fourth Annual International Neuropsychological Society Conference, February 1–4, 2006, Boston, Massachussetts, USA

2006 Journal of the International Neuropsychological Society  
Objective: Response inhibition (RI) is mediated by prefrontal cortex, its circuitry, and associated cortical regions that are vulnerable in traumatic brain injury (TBI).  ...  The current study used fMRI to study RI following TBI and to examine regressions with RI accuracy and reaction time.  ...  Perceptual biasing was also assessed for judgment of stimulus sweetness and weight.  ... 
doi:10.1017/s1355617706069918 fatcat:cy3cbwlgrvccfnn6w7inplceni

Final Program 2016 Mid-Year Meeting International Neuropsychological Society July 6–8, 2016 London, England

2016 Journal of the International Neuropsychological Society  
Objectives: Diffusion tractography is widely used for reconstructing white matter tracts in the living human brain and to correlate network anatomy with cognition and behaviour.  ...  and assists patient's relative for online supervision.  ...  The relatively rare central deletion (LCR-B-D) encompasses the CRKL gene and predominantly shows renal/urogenital anomalies in combination with autistic-like behaviours.  ... 
doi:10.1017/s1355617716001181 fatcat:7z6k6i6pazcufdcf6qtzphi6bq

Automated analysis of vascular structures of skin lesions : segmentation, pattern recognition and computer-aided diagnosis

Pegah Kharazmi
2019
The full abstract for this thesis is available in the body of the thesis, and will be available when the embargo expires.  ...  Comparison with Deep Networks (Unsupervised Feature Transfer) 4. Pre-trained CNN: Deep networks have recently dominated the unsupervised feature learning field.  ...  Smooth Segmentation: In this work, we only employed deep learning for patch-based segmentation of the vessels.  ... 
doi:10.14288/1.0365805 fatcat:x5t7nvkrk5fntpjpzk5ovxwz7a

Collaborative optimisation of focused anatomy observation and drawing techniques for enhancing cognitive memorisation. S149, (page 63). In: International Federation of Associations of Anatomists 19th Congress Abstracts 9th – 11th August 2019 London, UK

Leonard Shapiro, Iain Keenan
2020
Collaborative optimisation of focused anatomy observation and drawing techniques for enhancing cognitive memorisation. S149, (page 63).  ...  of their students' learning, yet the assessments we use for this have inherent biases.  ...  achieve deep learning.  ... 
doi:10.25375/uct.12824237 fatcat:i777oabeinfclgsi7ecwcve3sy

Supplementum 236: swiss orthopaedics, 79th annual meeting

2019 Swiss Medical Weekly  
The lung was easily dissected from the heart and aorta with its tissues to protect the tumor, except for the internal carotid artery which was end-to end-anastomosed after segmental resection.  ...  tibia plateau by semi-automatic segmentation of the corresponding CT scan.  ...  The American Society of Anesthesiologists' Score, gender, age, body mass index, diabetes, polyneuropathy, chronic renal failure, dialysis, peripheral arterial disease, smoking, and the antibiotic therapy  ... 
doi:10.4414/smw.2019.20438 fatcat:fruhdz3hwre5td4osxvycvey5a

Insomnia and inflammation: a two hit model of depression risk and prevention

Michael R. Irwin, Dominique Piber
2018 World Psychiatry  
Bierer and M.J. Meaney for their comments and very careful review of this paper, and A. Ropes for assistance with manuscript preparation.  ...  Roberts for help in the literature search, P. Kratochwill for assistance in full text acquisition and proof reading, Y. Zhu for help with screening and data extraction from Chinese studies, and C.  ...  METHODS Study design and participants The detailed methodology for this systematic review and network meta-analysis is described in the study protocol, that was registered a priori at PROSPERO (no.  ... 
doi:10.1002/wps.20556 pmid:30229570 pmcid:PMC6127743 fatcat:d5xaoj4yhbdkbnz7iymcb7tauy

Artificial magnetic resonance contrasts based on microvascular geometry: A numerical basis

Artur Hahn
2021
In this thesis, groundwork is laid for the exploration of such contrasts and suitable MRI sequences, with a demonstration of the feasibility of such an approach based on transverse relaxation for brain  ...  based on comparisons with known signals and ground-truth microstructure can be explored.  ...  Deep neural networks with an increasing number of hidden layers usually have an astronomical number of weights and connections to be tuned and, in practice, the adaptation of pre-trained network architectures  ... 
doi:10.11588/heidok.00030162 fatcat:l7cunjgg5fh6datc3ashvhnjiy

13. European Congress on Digital Pathology Berlin, May 25-28, 2016

Peter Hufnagl, Marcial Garcia Rojo, Frederick Klauschen
2016
There has also been an emergence of deep learning in digital histopathology for diverse classification and detection problems [6] - [8] .  ...  The first approach starts with a texture-based supervised classification to detect lobule candidate regions and uses a nuclear density image to refine the candidate regions.  ... 
doi:10.17629/www.diagnosticpathology.eu-2016-8:113 fatcat:nvpxgbl2ojbphfq5lcxyfvahpu

Program and Abstracts from the Canadian Digestive Diseases Week™2016

Canadian Association of Gastroenterology
2016 Canadian Journal of Gastroenterology and Hepatology  
Bacterial DNA extracted from the stool of 1098 healthy subject was sequenced for the V4 hypervariable regions of the 16S rRNA using the Illumina MiSeq platform.  ...  Association was performed using a linear regression controlling for age, gender and smoking status. Bacterial functions with a mean count <10 were excluded. Results.  ...  Funding Agencies: Gilead Sciences Canada for financial support of statistical analysis, None Acknowledgments. Jean Palmer for statistical analysis.  ... 
doi:10.1155/2016/4792898 pmid:27563641 pmcid:PMC4980872 fatcat:ti3volyn4bgu7fc7gs37bv6i5e
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