標題: Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019; 22nd International C Dinggang Shen,Tianming Liu,Ali Khan Conferen [打印本頁] 作者: 駝峰 時間: 2025-3-21 16:09
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019影響因子(影響力)
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019影響因子(影響力)學科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019網(wǎng)絡公開度
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019網(wǎng)絡公開度學科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019被引頻次
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019被引頻次學科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019年度引用
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019年度引用學科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019讀者反饋
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2019讀者反饋學科排名
作者: 流行 時間: 2025-3-21 21:11 作者: CURT 時間: 2025-3-22 03:16 作者: Mendicant 時間: 2025-3-22 05:09
Viswanath P. Sudarshan,Kratika Gupta,Gary Egan,Zhaolin Chen,Suyash P. Awate作者: barium-study 時間: 2025-3-22 11:44 作者: Pessary 時間: 2025-3-22 15:06
Kai Xuan,Dongming Wei,Dijia Wu,Zhong Xue,Yiqiang Zhan,Weiwu Yao,Qian Wang作者: maculated 時間: 2025-3-22 20:59
Elisabeth Hoppe,Florian Thamm,Gregor K?rzd?rfer,Christopher Syben,Franziska Schirrmacher,Mathias Nit作者: evaculate 時間: 2025-3-23 00:55 作者: POINT 時間: 2025-3-23 02:00 作者: abracadabra 時間: 2025-3-23 09:16
Pu Huang,Dengwang Li,Zhicheng Jiao,Dongming Wei,Guoshi Li,Qian Wang,Han Zhang,Dinggang Shen作者: 開頭 時間: 2025-3-23 13:39
Medical Image Computing and Computer Assisted Intervention – MICCAI 201922nd International C作者: 費解 時間: 2025-3-23 16:12 作者: 有毒 時間: 2025-3-23 19:28 作者: Genetics 時間: 2025-3-24 00:12
Yongsheng Pan,Mingxia Liu,Chunfeng Lian,Yong Xia,Dinggang Shensetzt, organisatorische Fragen in vier Stufen sinnvoll und effizient zu l?sen. Zu jedem Schritt werden Verknüpfungen mit der aktuellen Debatte sowie Vorschl?ge zur Umsetzung und praxistaugliche Instrumente vorgestellt. Checklisten und Tabellen erleichtern die individuelle Umsetzung im eigenen Unternehmen..978-3-658-16046-3作者: Inflamed 時間: 2025-3-24 03:41
Isotropic MRI Super-Resolution Reconstruction with Multi-scale Gradient Field Priorevaluated on the synthetic data as well as the data acquired on a Siemens 3T MRI scanner containing 45 MRI scans from 14 subjects. The evaluation results demonstrate that our proposed prior leads to improved SRR as compared to state-of-the-art priors, and that the proposed SRR obtains better results作者: barium-study 時間: 2025-3-24 07:11 作者: innovation 時間: 2025-3-24 14:12 作者: 費解 時間: 2025-3-24 15:35 作者: wangle 時間: 2025-3-24 20:12
Reconstruction of Isotropic High-Resolution MR Image from Multiple Anisotropic Scans Using Sparse Fipearance perceptually. Different from other SR methods, our approach fuses inputs of multiple anisotropic images, instead of a single one. Moreover, our reconstruction is attained without using any supervision from the isotropic high-resolution images, making it unique among early works and highly a作者: 阻擋 時間: 2025-3-25 01:05
Single Image Based Reconstruction of High Field-Like MR Imagesginal 3T & 7T and registered 3T MR image. This relation is used to constrain the solution space for 7T-like MR image reconstruction. The proposed algorithm provides comparable performance to the existing algorithms which require 3T-7T images pair. The qualitative and quantitative analysis is done fo作者: 動脈 時間: 2025-3-25 04:41 作者: 混沌 時間: 2025-3-25 07:30 作者: falsehood 時間: 2025-3-25 12:28 作者: 造反,叛亂 時間: 2025-3-25 17:23 作者: Crepitus 時間: 2025-3-25 21:31 作者: PAN 時間: 2025-3-26 03:27 作者: 文件夾 時間: 2025-3-26 06:30
Predicting the Evolution of White Matter Hyperintensities in Brain MRI Using Generative Adversarial tion of WMH in small vessel disease. DEP-GAN is able to estimate WMH volume in the follow-up year with mean (std) estimation error of ?1.91 (12.12)?ml and predict WMH evolution with mean rate of . accuracy (i.e., . and . better than Wasserstein GAN).作者: 食品室 時間: 2025-3-26 09:12 作者: Minuet 時間: 2025-3-26 13:52 作者: Negotiate 時間: 2025-3-26 20:19
Model Learning: Primal Dual Networks for Fast MR Imagingstruction model is finally learned from the training data by updating in k-space and image domain alternatively. Experiments on in vivo MR data demonstrate that the proposed method achieves superior MR reconstructions from highly undersampled k-space data over other state-of-the-art image reconstruction methods.作者: Defense 時間: 2025-3-26 22:55
Deep Gated Convolutional Neural Network for QSM Background Field Removals neural network was evaluated relative to established background removal methods using 100 . gold standard datasets and clinical susceptibility-weighted imaging datasets. Quantitative and qualitative assessment of the network performance demonstrated the benefits of the trained neural network.作者: 帶來墨水 時間: 2025-3-27 05:06
0302-9743 nce on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019...The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topi作者: gout109 時間: 2025-3-27 07:25 作者: ESO 時間: 2025-3-27 10:28
Deep Learning Based Framework for Direct Reconstruction of PET Imagesel. To verify the accuracy and robustness of the model, both Monte Carlo simulation data and real data are adopted in the test. The experimental results show that the proposed framework is of great robustness and the reconstructed image is much more accurate in comparison with the traditional methods.作者: 使乳化 時間: 2025-3-27 14:53
Conference proceedings 2019ical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019...The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sectio作者: COWER 時間: 2025-3-27 18:26
Mahmoud Mostapha,Juan Prieto,Veronica Murphy,Jessica Girault,Mark Foster,Ashley Rumple,Joseph Bloche, praxisorientiert und mit Vorschl?gen zur erfolgreichen UmsDieses Fachbuch bietet Führungskr?ften einen kompakten überblick über die Formen der Arbeitsteilung und der Koordination, mit denen sie ihrem Unternehmen eine Organisation geben, die zu ihren Zielen und Werten passt. Daniel Marek zeigt, wie作者: 或者發(fā)神韻 時間: 2025-3-28 00:28 作者: 不愛防注射 時間: 2025-3-28 02:53 作者: Mystic 時間: 2025-3-28 06:53 作者: Encoding 時間: 2025-3-28 14:21
Model Learning: Primal Dual Networks for Fast MR Imagingver, image reconstruction from undersampled k-space data is an ill-posed inverse problem. Iterative algorithms based on compressed sensing have been used to address the issue. In this work, we unroll the iterations of the primal-dual hybrid gradient algorithm to a learnable deep network architecture作者: OATH 時間: 2025-3-28 14:37 作者: Outmoded 時間: 2025-3-28 21:35 作者: 遺傳 時間: 2025-3-29 00:38
Deep Learning Based Framework for Direct Reconstruction of PET Imagesase. In this paper, we propose a deep learning based framework for PET image reconstruction from sinogram domain directly. In the framework, conditional Generative Adversarial Networks (cGANs) is constructed to learn a mapping from sinogram data to reconstructed image and generate a well-trained mod作者: Armada 時間: 2025-3-29 06:05
Nonuniform Variational Network: Deep Learning for Accelerated Nonuniform MR Image Reconstruction most works are limited in the sense that they assume equidistant rectilinear (Cartesian) data acquisition in 2D or 3D. In practice, a reconstruction from nonuniform samplings such as radial and spiral is an attractive choice for more efficient acquisitions. Nevertheless, it has less been explored a作者: Hallowed 時間: 2025-3-29 11:03
Reconstruction of Isotropic High-Resolution MR Image from Multiple Anisotropic Scans Using Sparse FiThe acquired images are thus anisotropic, with much lower inter-slice resolution than the intra-slice resolution. For better coverage of the organs of interest, multiple anisotropic scans, each of which focus to a certain scan direction, are usually acquired per patient. In this work, we propose a 3作者: 俗艷 時間: 2025-3-29 12:23 作者: Highbrow 時間: 2025-3-29 16:16
Deep Gated Convolutional Neural Network for QSM Background Field Removalication of tissue magnetism within a volume of interest (VOI). Conventional state-of-the-art QSM background removal methods suffer from several limitations in accuracy and performance. To overcome these limitations, a 3D gated convolutional neural network was trained to infer whole brain local tissu作者: 溫順 時間: 2025-3-29 19:58 作者: Fsh238 時間: 2025-3-30 03:49
RCA-U-Net: Residual Channel Attention U-Net for Fast Tissue Quantification in Magnetic Resonance Finoperties, such as T1 and T2 relaxation times, in one acquisition. To accelerate the data sampling in MRF, a variety of methods have been proposed to extract tissue properties from highly accelerated MRF signals. While these methods have demonstrated promising results, further improvement in the accu作者: STEER 時間: 2025-3-30 04:38
GANReDL: Medical Image Enhancement Using a Generative Adversarial Network with Real-Order Derivativeing and super-resolution, for instance). However, the central issue of recovering finer texture details in images still remains unsolved. State-of-the-art objective functions used in DCNN mostly focus on minimizing the mean squared reconstruction error. The resulting image estimates have high peak s作者: 單片眼鏡 時間: 2025-3-30 11:18 作者: fledged 時間: 2025-3-30 14:22 作者: 花爭吵 時間: 2025-3-30 17:59 作者: 乏味 時間: 2025-3-30 23:28 作者: galley 時間: 2025-3-31 04:54
CoCa-GAN: Common-Feature-Learning-Based Context-Aware Generative Adversarial Network for Glioma Gradcomplete set of high-resolution multi-modality data is costly and often impossible to acquire in clinical settings (although T1 MRI is more commonly acquired). To leverage more comprehensive multimodality information for better glioma grading instead of doing so with T1 MRI data only, we introduce a作者: 隱藏 時間: 2025-3-31 07:27 作者: 托人看管 時間: 2025-3-31 11:48
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019978-3-030-32248-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Fretful 時間: 2025-3-31 15:37
https://doi.org/10.1007/978-3-030-32248-9artificial intelligence; computed tomography; computer aided diagnosis; computer assisted interventions作者: CLOUT 時間: 2025-3-31 18:02 作者: 盡管 時間: 2025-4-1 00:48
Der Produktzustand als Basis für die Entwicklung produktnaher Dienstleistungendes Produktes, Nutzungsart und Umgebungsbedingungen. In diesem Kontext k?nnen Dienstleistungen angeboten werden, indem die Verantwortung für einige oder alle dieser Regelgr??en übernommen wird. Wird der Nutzungsprozess vollst?ndig durch einen Dienstleister durchgeführt, so kann ein Zielzustand Gegen作者: PALL 時間: 2025-4-1 03:45
Andreas Voellmy,Paul Hudakcrucial issue of how to optimally integrate biological markers, new technologies and new diagnostic and therapeutic approaches into clinical trials and clinical practice is addressed...Combining the contributio978-3-662-51762-8978-3-540-28266-2作者: 畫布 時間: 2025-4-1 08:20 作者: 通便 時間: 2025-4-1 13:57 作者: 衰弱的心 時間: 2025-4-1 17:56
