標題: 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: proptosis 時間: 2025-3-21 19:41
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讀者反饋學科排名
作者: laceration 時間: 2025-3-21 23:01 作者: 常到 時間: 2025-3-22 02:53
Lie Ju,Xin Wang,Lin Wang,Tongliang Liu,Xin Zhao,Tom Drummond,Dwarikanath Mahapatra,Zongyuan Getens wird auf klassische Fragen loser Kopplung sowie auf Diffusionsaspekte und die Transformation von Organisationen hin zu verantwortlichen Kollektivakteuren eingegangen. Zweitens werden ausgew?hlte Weiterentwicklungen beleuchtet; die Wiederentdeckung von Werten als Bezugspunkte organisationalen En作者: champaign 時間: 2025-3-22 08:30 作者: 不再流行 時間: 2025-3-22 12:44 作者: 辮子帶來幫助 時間: 2025-3-22 15:28
Sharif Amit Kamran,Khondker Fariha Hossain,Alireza Tavakkoli,Stewart Lee Zuckerbrod,Kenton M. Sanderher Kategorien organisationssoziologisch zu verstehen und zu erkl?ren ist. Anhand von?26 Interviews mit Compliance Officers multinationaler Unternehmen werden feldspezifische Deutungs- und Handlungsregeln rekonstruiert. An ihnen wird geprüft, ob im Sinne des Neo-Institutionalismus von einer Entkoppl作者: dowagers-hump 時間: 2025-3-22 17:13
Shuang Yu,Kai Ma,Qi Bi,Cheng Bian,Munan Ning,Nanjun He,Yuexiang Li,Hanruo Liu,Yefeng Zhengokussiert werden die Bemühungen von Organisationen, bestimmte Wertkomplexe in Transformationsfeldern, hier diskutiert an den Beispielen des Klimawandels und der Integration von Geflüchteten, relevant zu machen. Bei diesen Wertkomplexen handelt es sich um eine Verflechtung von Innovationen und altern作者: POLYP 時間: 2025-3-22 23:10 作者: 六個才偏離 時間: 2025-3-23 02:31 作者: 微粒 時間: 2025-3-23 06:46 作者: 分離 時間: 2025-3-23 13:42 作者: 啤酒 時間: 2025-3-23 17:15
Zeyu Gao,Jiangbo Shi,Xianli Zhang,Yang Li,Haichuan Zhang,Jialun Wu,Chunbao Wang,Deyu Meng,Chen Liern des modernen Naturrechts der Inklusion (also der Vermeidung sozialer Exklusion). Man kann auf einer grunds?tzlichen Ebene diskutieren, ob es (auch im Lichte der Corona-Krisen-Erfahrungen zur ?Kasernierung? alter Menschen in Pflegeeinrichtungen) nicht ein Moratorium als Stopp der weiteren Kontrah作者: incredulity 時間: 2025-3-23 21:23 作者: Virtues 時間: 2025-3-23 22:50
S. Shailja,Angela Zhang,B. S. Manjunath dieser Unternehmen, mit Konsequenzen für ihren organisatorischen und strukturellen Aufbau. Bettina Bürkin entwickelt in dieser Arbeit ein ganzheitliches Transformationsmodell mit dem Schwerpunkt der Dualit?t für diese Servicetransformation und leistet so einen konzeptionellen und praktischen Beitra作者: 者變 時間: 2025-3-24 06:15 作者: 惡心 時間: 2025-3-24 09:35 作者: 能量守恒 時間: 2025-3-24 13:12
Distinguishing Differences Matters: Focal Contrastive Network for Peripheral Anterior Synechiae Recof irreversible angle-closure glaucoma. Clinical identification of PAS requires indentation gonioscopy, which is patient-contacting and time-consuming. Thus, we aim to design an automatic deep-learning-based method for PAS recognition based on non-contacting anterior segment optical coherence tomogra作者: Aboveboard 時間: 2025-3-24 17:47
RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs Using a Novel Multi-scale Generayet it is a difficult problem. Due to successive resolution loss in the encoding phase combined with the inability to recover this lost information in the decoding phase, autoencoding based segmentation approaches are limited in their ability to extract retinal microvascular structure. We propose RV作者: Albinism 時間: 2025-3-24 19:59 作者: caldron 時間: 2025-3-25 01:15
Local-Global Dual Perception Based Deep Multiple Instance Learning for Retinal Disease Classificatioetinal disease recognition. The unique characteristics of how retinal diseases are manifested on the fundus images pose a major challenge for automatic recognition. In order to tackle the challenges, we propose a local-global dual perception (LGDP) based deep multiple instance learning (MIL) framewo作者: 決定性 時間: 2025-3-25 05:46
BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifyinar zone (FAZ) across retinal layers. Clinical researches suggest that the morphology and contour irregularity of FAZ are important biomarkers of various ocular pathologies. Therefore, precise segmentation of FAZ has great clinical interest. Also, there is no existing research reporting that FAZ feat作者: 珊瑚 時間: 2025-3-25 09:34 作者: 分開如此和諧 時間: 2025-3-25 13:36 作者: CESS 時間: 2025-3-25 17:17 作者: FEIGN 時間: 2025-3-25 20:37
Simultaneous Alignment and Surface Regression Using Hybrid 2D-3D Networks for 3D Coherent Layer Segmning based methods have been developed for this task and yield remarkable performance. However, due to large spatial gap and potential mismatch between the B-scans of OCT data, all of them are based on 2D segmentation of individual B-scans, which may loss the continuity information across the B-scan作者: 可憎 時間: 2025-3-26 02:13 作者: trigger 時間: 2025-3-26 04:48 作者: pester 時間: 2025-3-26 11:36
Prototypical Models for Classifying High-Risk Atypical Breast Lesionss. We reframe the computational diagnosis of atypical breast lesions as a problem of prototype recognition on the basis that pathologists mentally relate current histological patterns to previously encountered patterns during their routine diagnostic work. In an unsupervised manner, we investigate t作者: 似少年 時間: 2025-3-26 16:31 作者: 從屬 時間: 2025-3-26 17:20
Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasmsd topic in computational pathology. This study, to the best of our knowledge, is among the first to hybridize local and global graph methods to profile orchestration and interaction of cellular components. To address the challenge in hematolymphoid cancers, where the cell classes in TME may be uncle作者: 新陳代謝 時間: 2025-3-27 00:28
A Computational Geometry Approach for?Modeling Neuronal Fiber Pathwaysers in three dimensions that exhibit the geometry of white matter pathways in the brain. However, most tractography analysis methods are time consuming and intractable. We develop a computational geometry-based tractography representation that aims to simplify the connectivity of white matter fibers作者: ANTE 時間: 2025-3-27 04:00 作者: phytochemicals 時間: 2025-3-27 07:56
LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos network to segment the lens and pupil after the implantation phase. The phase recognition results reveal the effectiveness of the proposed surgical phase recognition approach. Moreover, the segmentation results confirm the proposed segmentation network’s effectiveness compared to state-of-the-art rival approaches.作者: 委派 時間: 2025-3-27 09:55 作者: 我邪惡 時間: 2025-3-27 16:56
A Computational Geometry Approach for?Modeling Neuronal Fiber Pathwaysws local or global representation of the tractogram. Using diffusion MRI data from Alzheimer’s patient study, we extract tractography features from our model for distinguishing the Alzheimer’s subject from the normal control. Software implementation of our algorithm is available on GitHub (.).作者: insert 時間: 2025-3-27 21:18 作者: GEAR 時間: 2025-3-27 23:19 作者: Armada 時間: 2025-3-28 02:58
https://doi.org/10.1007/978-3-030-87237-3artificial intelligence; color image processing; computer aided diagnosis; computer assisted interventi作者: itinerary 時間: 2025-3-28 08:25
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/629209.jpg作者: 急急忙忙 時間: 2025-3-28 12:30 作者: Adulate 時間: 2025-3-28 15:01 作者: exceptional 時間: 2025-3-28 21:17
0302-9743 and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality..Part V: computer aided diagnosis; i978-3-030-87236-6978-3-030-87237-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 群島 時間: 2025-3-29 02:51
Li Lin,Zhonghua Wang,Jiewei Wu,Yijin Huang,Junyan Lyu,Pujin Cheng,Jiong Wu,Xiaoying Tang作者: Agility 時間: 2025-3-29 03:27
Negin Ghamsarian,Mario Taschwer,Doris Putzgruber-Adamitsch,Stephanie Sarny,Yosuf El-Shabrawi,Klaus S作者: flaggy 時間: 2025-3-29 09:20
Hong Liu,Dong Wei,Donghuan Lu,Yuexiang Li,Kai Ma,Liansheng Wang,Yefeng Zheng作者: 遭遇 時間: 2025-3-29 13:48 作者: Respond 時間: 2025-3-29 18:50
Jiangpeng Yan,Hanbo Chen,Kang Wang,Yan Ji,Yuyao Zhu,Jingjing Li,Dong Xie,Zhe Xu,Junzhou Huang,Shuqun作者: 貿(mào)易 時間: 2025-3-29 21:24 作者: 旋轉(zhuǎn)一周 時間: 2025-3-30 02:50 作者: frivolous 時間: 2025-3-30 07:51 作者: Vaginismus 時間: 2025-3-30 10:37 作者: NUDGE 時間: 2025-3-30 14:50 作者: 背心 時間: 2025-3-30 16:55
RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs Using a Novel Multi-scale Generatures from the discriminator’s decoder over the encoder. Doing so combined with the fact that the discriminator’s decoder attempts to determine real or fake images at the pixel level better preserves macro and microvascular structure. By combining reconstruction and weighted feature matching loss, t作者: peptic-ulcer 時間: 2025-3-31 00:09
MIL-VT: Multiple Instance Learning Enhanced Vision Transformer for Fundus Image Classificationniently attached to the Vision Transformer in a plug-and-play manner and effectively enhances the model performance for the downstream fundus image classification tasks. The proposed MIL-VT framework achieves superior performance over CNN models on two publicly available datasets when being trained 作者: 你正派 時間: 2025-3-31 01:59 作者: cunning 時間: 2025-3-31 08:34
BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifyinentation performance, resulting in more accurate FAZ contours and fewer outliers. Moreover, both low-level and high-level features from the aforementioned three branches, including shape, size, boundary, and signed directional distance map of FAZ, are fused hierarchically with features from the diag作者: 萬靈丹 時間: 2025-3-31 11:30 作者: ANIM 時間: 2025-3-31 13:36 作者: 陶器 時間: 2025-3-31 21:30
Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by?Composite High-Resol-category classification tasks that are leaned by two newly designed high-resolution feature extractors (HRFEs). The two HRFEs share the same backbone encoder with W-Net by a composite connection so that meaningful features for the segmentation task can be inherited to the classification task. Last,作者: 編輯才信任 時間: 2025-4-1 01:25
Prototypical Models for Classifying High-Risk Atypical Breast Lesionsing clinically relevant explanations to its recommendations, thus it is intrinsically explainable, which is a major contribution of this work. Our experiments also show state-of-the-art performance in recall compared to the latest deep-learning based graph neural networks (GNNs).作者: 漸變 時間: 2025-4-1 01:57
