標(biāo)題: Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2021; 24th International C Marleen de Bruijne,Philippe C. Cattin,Caroli [打印本頁] 作者: CT951 時間: 2025-3-21 19:12
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021影響因子(影響力)
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021影響因子(影響力)學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021網(wǎng)絡(luò)公開度
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021被引頻次
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021被引頻次學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021年度引用
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021年度引用學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021讀者反饋
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2021讀者反饋學(xué)科排名
作者: 運動吧 時間: 2025-3-21 23:13 作者: Congregate 時間: 2025-3-22 04:07
0302-9743 and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality..Part V: computer aided diagnosis; i978-3-030-87198-7978-3-030-87199-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Custodian 時間: 2025-3-22 07:45
Shuo Wang,Chen Qin,Nicolò Savioli,Chen Chen,Declan P. O’Regan,Stuart Cook,Yike Guo,Daniel Rueckert,Whe Einführung in die Architektur von Betriebssystemen und eignet sich deshalb auch für die Lehre im Bachelorstudium.?Memory management, hardware management, process administration and interprocess communication978-3-658-29785-5作者: 天氣 時間: 2025-3-22 12:22
Junyu Chen,Evren Asma,Chung Chanhe Einführung in die Architektur von Betriebssystemen und eignet sich deshalb auch für die Lehre im Bachelorstudium.?Memory management, hardware management, process administration and interprocess communication978-3-658-29785-5作者: Pandemic 時間: 2025-3-22 16:00 作者: 貴族 時間: 2025-3-22 17:49 作者: 要塞 時間: 2025-3-22 22:09 作者: achlorhydria 時間: 2025-3-23 03:53
Jens Petersen,Fabian Isensee,Gregor K?hler,Paul F. J?ger,David Zimmerer,Ulf Neuberger,Wolfgang Wick,作者: 含糊 時間: 2025-3-23 07:44
Jia-Ren Chang,Min-Sheng Wu,Wei-Hsiang Yu,Chi-Chung Chen,Cheng-Kung Yang,Yen-Yu Lin,Chao-Yuan Yeh作者: 并排上下 時間: 2025-3-23 10:57
Chen Chen,Kerstin Hammernik,Cheng Ouyang,Chen Qin,Wenjia Bai,Daniel Rueckert作者: 基因組 時間: 2025-3-23 17:09
Spyridon Thermos,Xiao Liu,Alison O’Neil,Sotirios A. Tsaftaris作者: 浮雕寶石 時間: 2025-3-23 21:11
Joint Motion Correction and Super Resolution for Cardiac Segmentation via?Latent Optimisation of cardiac imaging. To solve the inverse problem, iterative optimisation is performed in a latent space, which ensures the anatomical plausibility. This alleviates the need of paired low-resolution and high-resolution images for supervised learning. Experiments on two cardiac MR datasets show that 作者: 在前面 時間: 2025-3-24 00:48 作者: Heresy 時間: 2025-3-24 04:27
A Hierarchical Feature Constraint to?Camouflage Medical Adversarial Attacksint (HFC) as an add-on to existing white-box attacks, which encourages hiding the adversarial representation in the normal feature distribution. We evaluate the proposed method on two public medical image datasets, namely Fundoscopy and Chest X-Ray. Experimental results demonstrate the superiority o作者: Bph773 時間: 2025-3-24 06:51
Group Shift Pointwise Convolution for Volumetric Medical Image SegmentationTo address this problem, we propose a parameter-free operation, Group Shift (GS), which shifts the feature maps along different spatial directions in an elegant way. With GS, pointwise convolutions can access features from different spatial locations, and the limited receptive fields of pointwise co作者: 防御 時間: 2025-3-24 12:23
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentatione amounts of data to learn vision inductive bias. Our hybrid layer design allows the initialization of Transformer into convolutional networks without a need of pre-training. We have evaluated UTNet on the multi-label, multi-vendor cardiac magnetic resonance imaging cohort. UTNet demonstrates superi作者: gentle 時間: 2025-3-24 15:24
AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Gener abnormal regions of the input image, which could alleviate data bias problem; 2) MGT module effectively uses the multi-grained features and Transformer framework to generate the long medical report. The experiments on the public IU-Xray and MIMIC-CXR datasets show that the AlignTransformer can achi作者: 厭倦嗎你 時間: 2025-3-24 22:23 作者: 問到了燒瓶 時間: 2025-3-24 23:28 作者: Modify 時間: 2025-3-25 04:18 作者: 頂點 時間: 2025-3-25 10:35 作者: 相一致 時間: 2025-3-25 13:25 作者: Nebulizer 時間: 2025-3-25 16:33 作者: declamation 時間: 2025-3-25 22:35
Controllable Cardiac Synthesis via Disentangled Anatomy Arithmetiche target characteristics. To encourage a realistic combination of anatomy factors after the arithmetic step, we propose a localized noise injection network that precedes the generator. Our model is used to generate realistic images, pathology labels, and segmentation masks that are used to augment 作者: 未完成 時間: 2025-3-26 02:27 作者: Prostatism 時間: 2025-3-26 07:03 作者: 牛的細(xì)微差別 時間: 2025-3-26 11:29 作者: Expurgate 時間: 2025-3-26 12:48 作者: Connotation 時間: 2025-3-26 17:26
Conference proceedings 2021nference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*.The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in 作者: Mortar 時間: 2025-3-26 21:58
Towards Robust General Medical Image Segmentationframework to the domain of volumetric data segmentation, and . we present a novel lattice architecture for RObust Generic medical image segmentation (ROG). Our results show that ROG is capable of generalizing across different tasks of the MSD and largely surpasses the state-of-the-art under sophisticated adversarial attacks.作者: Lineage 時間: 2025-3-27 04:29 作者: 路標(biāo) 時間: 2025-3-27 07:41 作者: 斷言 時間: 2025-3-27 11:46
Shuo Wang,Chen Qin,Nicolò Savioli,Chen Chen,Declan P. O’Regan,Stuart Cook,Yike Guo,Daniel Rueckert,Wagenwissen zu Betriebssystemen im handlichen TaschenbuchformMemory management, hardware management, process administration and interprocess communication are central areas of operating systems. The concepts and principles on which classical and modern operating systems are based are explained by the作者: 噱頭 時間: 2025-3-27 17:22 作者: 憤憤不平 時間: 2025-3-27 19:51 作者: 糾纏,纏繞 時間: 2025-3-28 01:52 作者: 牲畜欄 時間: 2025-3-28 03:21 作者: 真實的人 時間: 2025-3-28 10:17
Joint Motion Correction and Super Resolution for Cardiac Segmentation via?Latent Optimisationructures. However, due to the limit of acquisition duration and respiratory/cardiac motion, stacks of multi-slice 2D images are acquired in clinical routine. The segmentation of these images provides a low-resolution representation of cardiac anatomy, which may contain artefacts caused by motion. He作者: ablate 時間: 2025-3-28 13:52
Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-Tuning and Online-Lvarious tasks often requires a complete training dataset that consists of images drawn from different tasks. In most scenarios, it is nearly impossible to collect every possible representative dataset as a priori. The new data may only become available after the ConvNet is deployed in clinical pract作者: 手銬 時間: 2025-3-28 18:33
A Hierarchical Feature Constraint to?Camouflage Medical Adversarial Attacksing. Recent findings have shown that existing medical AEs are easy to detect in feature space. To better understand this phenomenon, we thoroughly investigate the characteristic of traditional medical AEs in feature space. Specifically, we first perform a stress test to reveal the vulnerability of m作者: 1FAWN 時間: 2025-3-28 19:31 作者: Tdd526 時間: 2025-3-28 23:13
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentationmain largely unexplored. In this study, we present UTNet, a simple yet powerful hybrid Transformer architecture that integrates self-attention into a convolutional neural network for enhancing medical image segmentation. UTNet applies self-attention modules in both encoder and decoder for capturing 作者: 農(nóng)學(xué) 時間: 2025-3-29 03:23
AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generived growing research interests. Different from the general image captioning tasks, medical report generation is more challenging for data-driven neural models. This is mainly due to 1) the serious data bias: the normal visual regions dominate the dataset over the abnormal visual regions, and 2) the作者: Trochlea 時間: 2025-3-29 08:49
Continuous-Time Deep Glioma Growth Modelsse distribution in radiation therapy. Recent work has approached the glioma growth modeling problem via deep learning and variational inference, thus learning growth dynamics entirely from a real patient data distribution. So far, this approach was constrained to predefined image acquisition interva作者: outset 時間: 2025-3-29 14:06
Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Trael transformers-based 3D object detection method that views automatic detection of vertebrae in arbitrary FOV CT scans as an one-to-one set prediction problem. The main components of the new framework, called Spine-Transformers, are an one-to-one set based global loss that forces unique predictions 作者: OGLE 時間: 2025-3-29 18:38
Multi-view Analysis of Unregistered Medical Images Using Cross-View Transformersrms of misalignment can make it difficult to combine views effectively, as registration is not always possible. Without registration, views can only be combined at a global feature level, by joining feature vectors after global pooling. We present a novel cross-view transformer method to transfer in作者: 法律 時間: 2025-3-29 21:34 作者: 悲觀 時間: 2025-3-30 00:20 作者: Priapism 時間: 2025-3-30 05:33
Generative Self-training for Cross-Domain Unsupervised Tagged-to-Cine MRI Synthesisp learning model in a source domain to unlabeled target domains. However, while the self-training UDA has demonstrated its effectiveness on discriminative tasks, such as classification and segmentation, via the reliable pseudo-label selection based on the softmax discrete histogram, the self-trainin作者: 俗艷 時間: 2025-3-30 09:35 作者: SEEK 時間: 2025-3-30 14:43 作者: Ordnance 時間: 2025-3-30 16:34
CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentationthese networks, however, inevitably have limitations in modeling the long-range dependency due to their inductive bias of locality and weight sharing. Although Transformer was born to address this issue, it suffers from extreme computational and spatial complexities in processing high-resolution 3D 作者: AVID 時間: 2025-3-30 23:34
978-3-030-87198-7Springer Nature Switzerland AG 2021作者: Occupation 時間: 2025-3-31 03:55 作者: 主動脈 時間: 2025-3-31 07:41
https://doi.org/10.1007/978-3-030-87199-4artificial intelligence; bioinformatics; color image processing; computer aided diagnosis; computer assi作者: 白楊魚 時間: 2025-3-31 11:53 作者: 意外 時間: 2025-3-31 15:38 作者: semiskilled 時間: 2025-3-31 21:04 作者: 樂器演奏者 時間: 2025-4-1 01:03
Entwicklung eines Katalogs von Regulationsmustern zur Unterstützung der Compliance-überprüfung von Gn Jahren ist eine ganze Reihe von BPCC-Ans?tzen entwickelt worden. Die Ans?tze zeigen, dass das BPCC methodisch bereits gut unterstützt wird. Konkrete Listen oder Kataloge von Regulationsmustern existieren hingegen bisher kaum. Damit fehlt es BPCC-Ans?tzen weithin an konkreten Inputs. Im Rahmen dies作者: Polydipsia 時間: 2025-4-1 05:22
Julio Mari?o,Juan José Moreno-Navarro treatment under a more comprehensive light, and is a valuable resource for any Radiation or Surgical Oncologist, Cancer Biologist or Pathologist..978-1-60761-466-1978-1-60327-945-1Series ISSN 2364-1134 Series E-ISSN 2364-1142 作者: MILK 時間: 2025-4-1 08:58
Jürgen E. K. Schawe,Stefan Pogatscher Lichtreizen Potential?nderungen gleicher Frequenz im okzipitalen EEG nachweisen. Mit Hilfe des Einsatzes moderner elektronischer Ger?te war dann dank der klinischen Einführung durch Ciganek (1961,1967) und Halliday (1963) die M?glichkeit erreicht, bisher nur in der subjektiven Empfindungsskala me?b作者: patriot 時間: 2025-4-1 10:53
https://doi.org/10.1007/978-3-319-95591-9Ulcerative colitis; Crohn′s colitis; Familial adenomatous polyposis; Proctocolectomy; Reconstruction; Inf作者: OGLE 時間: 2025-4-1 16:42
,Einführung,en behandelt (L. U. M. 1992). Die Behandlung dieser Rhythmusst?rungen war bis vor kurzem noch die Dom?ne der medikament?sen Therapie. H?ufiges Therapieversagen, proarrhythmische Effekte und die Notwendigkeit einer jahrzehntelangen Medikamenteneinnahme haben zur Entwicklung alternativer, d.h. nichtme
