標(biāo)題: Titlebook: Bayesian and grAphical Models for Biomedical Imaging; First International M. Jorge Cardoso,Ivor Simpson,Annemie Ribbens Conference proceed [打印本頁(yè)] 作者: 我贊成 時(shí)間: 2025-3-21 19:44
書(shū)目名稱Bayesian and grAphical Models for Biomedical Imaging影響因子(影響力)
書(shū)目名稱Bayesian and grAphical Models for Biomedical Imaging影響因子(影響力)學(xué)科排名
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書(shū)目名稱Bayesian and grAphical Models for Biomedical Imaging網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
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書(shū)目名稱Bayesian and grAphical Models for Biomedical Imaging讀者反饋
書(shū)目名稱Bayesian and grAphical Models for Biomedical Imaging讀者反饋學(xué)科排名
作者: appall 時(shí)間: 2025-3-21 23:48
Conference proceedings 2014ical imaging, have a stronger mathematical focus on the foundations of probabilistic modeling and inference. The papers highlight the potential of using Bayesian or random field graphical models for advancing scientific research in biomedical image analysis or for the advancement of modeling and analysis of medical imaging data.作者: 變量 時(shí)間: 2025-3-22 01:43
Lecture Notes in Computer Sciencere weighted ?.-norm minimization. Experiments on a digital phantom and . tongue diffusion data demonstrate that the proposed method is able to resolve crossing fibers with limited gradient directions.作者: Embolic-Stroke 時(shí)間: 2025-3-22 06:04 作者: 秘傳 時(shí)間: 2025-3-22 09:33
A Bayesian Approach to Distinguishing Interdigitated Muscles in the Tongue from Limited Diffusion Wre weighted ?.-norm minimization. Experiments on a digital phantom and . tongue diffusion data demonstrate that the proposed method is able to resolve crossing fibers with limited gradient directions.作者: FUSC 時(shí)間: 2025-3-22 15:37 作者: foppish 時(shí)間: 2025-3-22 20:55
N3 Bias Field Correction Explained as a Bayesian Modeling Method,l strategies as expectation maximization (EM) based bias field correction methods. We demonstrate experimentally that purely EM-based methods are capable of producing bias field correction results comparable to those of N3 in less computation time.作者: dissent 時(shí)間: 2025-3-22 22:42 作者: 思想流動(dòng) 時(shí)間: 2025-3-23 02:03
Four Neuroimaging Questions that P-Values Cannot Answer (and Bayesian Analysis Can),that we formulate as four research questions insoluble with .-values. We demonstrate how, in theory, Bayesian approaches can provide answers to such questions. We discuss the implications of these questions as well as the practicalities of such approaches in neuroimaging.作者: musicologist 時(shí)間: 2025-3-23 09:10 作者: 損壞 時(shí)間: 2025-3-23 12:42 作者: macrophage 時(shí)間: 2025-3-23 16:50
Bone Reposition Planning for Corrective Surgery Using Statistical Shape Model: Assessment of Differroperties for planning, different geometrical features of the bone surface are being incorporated. The feasibility and accuracy of our proposed method are investigated using 10 virtually deformed radii and a statistical shape model based on 35 healthy radii.作者: 糾纏 時(shí)間: 2025-3-23 19:57
Yuta Sudo,Toru Nakata,Toshikazu Katol strategies as expectation maximization (EM) based bias field correction methods. We demonstrate experimentally that purely EM-based methods are capable of producing bias field correction results comparable to those of N3 in less computation time.作者: 不透氣 時(shí)間: 2025-3-24 01:33
Tania Roy,Larry F. Hodges,Fehmi Neffatin this work we consider a model of both hemodynamic and perfusion components within the ASL signal. A physiological link between these two components is analyzed and used for a more accurate estimation of the perfusion response function in particular in the usual ASL low SNR conditions.作者: exostosis 時(shí)間: 2025-3-24 04:28 作者: 猜忌 時(shí)間: 2025-3-24 08:45
Liheng Yang,Yoshihiro Sejima,Tomio Watanabeaccelerated primitives specializes iLang to the spatial data-structures that arise in imaging applications. We illustrate the framework through a challenging application: spatio-temporal tomographic reconstruction with compressive sensing.作者: Capture 時(shí)間: 2025-3-24 12:00 作者: Firefly 時(shí)間: 2025-3-24 15:11 作者: Innovative 時(shí)間: 2025-3-24 20:53
,Learning Imaging Biomarker Trajectories from Noisy Alzheimer’s Disease Data Using a Bayesian Multilestimation to avoid regression dilution bias. Applicable to any disease, here we perform experiments on Alzheimer’s disease imaging biomarker data — volumes of regions of interest within the brain. We find that Alzheimer’s disease imaging biomarkers are dynamic over timescales from a few years to a few decades.作者: 隱藏 時(shí)間: 2025-3-25 02:26
0302-9743 ial of using Bayesian or random field graphical models for advancing scientific research in biomedical image analysis or for the advancement of modeling and analysis of medical imaging data.978-3-319-12288-5978-3-319-12289-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: grotto 時(shí)間: 2025-3-25 05:11
Kaifeng Lei,Yoko Nishihara,Ryosuke Yamanishi type of constraint that ensures that cells exit the Mother Machine in the correct order. Our method finds a globally optimal tracking solution with an accuracy of >?95% (1.22 times the inter-observer error) and is on average 2???11 times faster than the microscope produces the raw data.作者: 繼而發(fā)生 時(shí)間: 2025-3-25 10:24 作者: 青石板 時(shí)間: 2025-3-25 11:51 作者: 貧窮地活 時(shí)間: 2025-3-25 19:24
Optimal Joint Segmentation and Tracking of , in the Mother Machine, type of constraint that ensures that cells exit the Mother Machine in the correct order. Our method finds a globally optimal tracking solution with an accuracy of >?95% (1.22 times the inter-observer error) and is on average 2???11 times faster than the microscope produces the raw data.作者: detach 時(shí)間: 2025-3-25 23:21 作者: 提名的名單 時(shí)間: 2025-3-26 03:16 作者: Firefly 時(shí)間: 2025-3-26 05:37
Bayesian and grAphical Models for Biomedical ImagingFirst International 作者: nocturia 時(shí)間: 2025-3-26 09:23 作者: BLA 時(shí)間: 2025-3-26 16:08
A Bayesian Approach to Distinguishing Interdigitated Muscles in the Tongue from Limited Diffusion Wsue. However, in cases where only a limited number of gradient directions can be acquired, for example in the tongue, the multi-tensor models fail to resolve the crossing correctly due to insufficient information. In this work, we address this challenge by using a fixed tensor basis and incorporatin作者: 工作 時(shí)間: 2025-3-26 18:58
Optimal Joint Segmentation and Tracking of , in the Mother Machine,ns (growth channels) in a so-called “Mother Machine” [1]. In these growth channels, cells are vertically aligned, grow and divide over time, and eventually leave the channel at the top. The model is built on a large set of cell segmentation hypotheses for each video frame that we extract from data u作者: 偏見(jiàn) 時(shí)間: 2025-3-27 00:00 作者: 無(wú)意 時(shí)間: 2025-3-27 01:26
Bone Reposition Planning for Corrective Surgery Using Statistical Shape Model: Assessment of Differhape model to estimate the most likely relative position of two bone segments of an osteotomized bone. To investigate the added value of geometrical properties for planning, different geometrical features of the bone surface are being incorporated. The feasibility and accuracy of our proposed method作者: DEI 時(shí)間: 2025-3-27 05:54 作者: 彎彎曲曲 時(shí)間: 2025-3-27 10:36
An MRF-Based Discrete Optimization Framework for Combined DCE-MRI Motion Correction and Pharmacokined by motion, which causes significant errors in tracer kinetic model analysis. Current intra-sequence registration methods for contrast enhanced data either assume restricted transformations (e.g. translation) or employ continuous optimization, which is prone to local optima. In this work, we propo作者: 火光在搖曳 時(shí)間: 2025-3-27 13:56
,Learning Imaging Biomarker Trajectories from Noisy Alzheimer’s Disease Data Using a Bayesian Multilvely long and expensive. Considering what can be learned in the absence of such data, we estimate cohort-level biomarker trajectories by fitting cross-sectional data to a differential equation model, then integrating the fit. These fits inform our new stochastic differential equation model for synth作者: Frisky 時(shí)間: 2025-3-27 18:27
Four Neuroimaging Questions that P-Values Cannot Answer (and Bayesian Analysis Can),s have mostly focused on technical issues with multiple comparisons and difficulties in interpreting .-values. While these critiques are valuable, we believe that they overlook the fundamental flaws of NHST in answering research questions. In this paper, we review major limitations inherent to NHST 作者: 殘廢的火焰 時(shí)間: 2025-3-27 23:26
Spherical Topic Models for Imaging Phenotype Discovery in Genetic Studies,or each subject is provided as a normalized histogram of relevant features. In this paper, the resulting descriptors are used as phenotypes to identify genetic markers associated with the Chronic Obstructive Pulmonary Disease (COPD). Features extracted from images capture the heterogeneity of the di作者: notion 時(shí)間: 2025-3-28 02:49
A Generative Model for Automatic Detection of Resolving Multiple Sclerosis Lesions,turn to isointensity. This resolution is thought to be due mostly to reabsorption of edema, but may also reflect other reparatory processes such as remyelination. Automatic identification of resolving portions of new lesions can provide a marker of repair, allow for automated analysis of MS lesion d作者: jettison 時(shí)間: 2025-3-28 06:16 作者: Trigger-Point 時(shí)間: 2025-3-28 11:01
Yuta Sudo,Toru Nakata,Toshikazu Katoy, the method relies on a relatively heuristic recipe of alternating iterative steps that does not optimize any particular objective function. In this paper we explain the successful bias field correction properties of N3 by showing that it implicitly uses the same generative models and computationa作者: 爭(zhēng)論 時(shí)間: 2025-3-28 15:50
Lecture Notes in Computer Sciencesue. However, in cases where only a limited number of gradient directions can be acquired, for example in the tongue, the multi-tensor models fail to resolve the crossing correctly due to insufficient information. In this work, we address this challenge by using a fixed tensor basis and incorporatin作者: confide 時(shí)間: 2025-3-28 21:43 作者: RALES 時(shí)間: 2025-3-29 02:41 作者: grandiose 時(shí)間: 2025-3-29 04:40
Lecture Notes in Computer Sciencehape model to estimate the most likely relative position of two bone segments of an osteotomized bone. To investigate the added value of geometrical properties for planning, different geometrical features of the bone surface are being incorporated. The feasibility and accuracy of our proposed method
