標(biāo)題: Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022; 25th International C Linwei Wang,Qi Dou,Shuo Li Conference procee [打印本頁] 作者: 爆裂 時間: 2025-3-21 17:56
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022影響因子(影響力)
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022影響因子(影響力)學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022網(wǎng)絡(luò)公開度
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022被引頻次
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022被引頻次學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022年度引用
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022年度引用學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022讀者反饋
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2022讀者反饋學(xué)科排名
作者: NAUT 時間: 2025-3-21 20:18
n, wo klassische Au?enwerbung wie Plakatw?nde und Poster – zunehmend aber auch digitale Au?enwerbung in Form von Digitalen City-Light-Postern oder Roadside Screens – zu finden ist. Die verbleibenden 97?% der Werbefl?chen befinden sich in Innenr?umen – in Einkaufszentren, Superm?rkten, Bahnh?fen und 作者: 昏迷狀態(tài) 時間: 2025-3-22 03:26
Chao Xia,Jiyue Wang,Yulei Qin,Yun Gu,Bing Chen,Jie Yangn, wo klassische Au?enwerbung wie Plakatw?nde und Poster – zunehmend aber auch digitale Au?enwerbung in Form von Digitalen City-Light-Postern oder Roadside Screens – zu finden ist. Die verbleibenden 97?% der Werbefl?chen befinden sich in Innenr?umen – in Einkaufszentren, Superm?rkten, Bahnh?fen und 作者: 藕床生厭倦 時間: 2025-3-22 04:50
Xiaoyu Liu,Bo Hu,Wei Huang,Yueyi Zhang,Zhiwei Xiongturen und der ?ffentlichen Hand auf. Es richtet sich an Marketing-Entscheider, Werbungtreibende, Designer, Media- und Werbeagenturen sowie kommunale Entscheidungstr?ger. Die Autoren – allesamt ausgewiesene Experten, Macher und Vordenker der OOH-Kommunikation – durchleuchten die komplexen ?sthetische作者: Genistein 時間: 2025-3-22 12:21
Peter Hirsch,Caroline Malin-Mayor,Anthony Santella,Stephan Preibisch,Dagmar Kainmueller,Jan Funken, wo klassische Au?enwerbung wie Plakatw?nde und Poster – zunehmend aber auch digitale Au?enwerbung in Form von Digitalen City-Light-Postern oder Roadside Screens – zu finden ist. Die verbleibenden 97?% der Werbefl?chen befinden sich in Innenr?umen – in Einkaufszentren, Superm?rkten, Bahnh?fen und 作者: 尊重 時間: 2025-3-22 16:22 作者: Gleason-score 時間: 2025-3-22 19:37
Jun Wu,Bo Shen,Hanwen Zhang,Jianing Wang,Qi Pan,Jianfeng Huang,Lixin Guo,Jianchun Zhao,Gang Yang,Xirs continuity and governance on the other. The growing number of regulations, e.g., on information security, data protection, or privacy, implemented in increasingly digitized businesses can have an obstructive effect on the automated execution of business processes. Such security-related obstruction作者: 多山 時間: 2025-3-22 23:55 作者: 主動 時間: 2025-3-23 01:55
Lin Li,Jingyi Liu,Shuo Wang,Xunkun Wang,Tian-Zhu Xiangeir consequences. Today, humanity‘s energy needs are largely met in ways that are harmful to the climate. The alternative to this, solar energy, would satisfy our needs thousands of times over. But this option is far too little used for mainly economic reasons. This essential then discusses the ener作者: 倒轉(zhuǎn) 時間: 2025-3-23 06:11
Qilong Zhangli,Jingru Yi,Di Liu,Xiaoxiao He,Zhaoyang Xia,Qi Chang,Ligong Han,Yunhe Gao,Song Wen,Haima positive view of humanity, a deeply rooted optimism, the ability to trust others, as well as an inner call for and joy in leadership. Leading people means to serve people, to guide and accompany them, to sense what the other person needs in order to recognize his or her potential. I speak of excel作者: Enteropathic 時間: 2025-3-23 11:42
Yeman Brhane Hagos,Ayse U Akarca,Alan Ramsay,Riccardo L Rossi,Sabine Pomplun,Alessia Moioli,Andrea Gthis chapter, which presents various onboarding scenarios and provides concrete recommendations for action that have proven successful over a very long period of leadership practice. These four scenarios range from an initial team leader role to taking over an organization with leaders. The recommen作者: 厭煩 時間: 2025-3-23 14:28
Dominik J. E. Waibel,Scott Atwell,Matthias Meier,Carsten Marr,Bastian Rieckn professional ethics, the patient‘s wishes and behavior, legal norms, and unwritten or formal rules of the organization. Such dilemma situations may lead to delinquency such as the manipulation of data and the alteration of medication to influence the ranking of allocation of a donor organ in patie作者: 騎師 時間: 2025-3-23 19:18
essure to develop effective compliance management systems (CMS) for preventing, identifying, and prosecuting violations. Against this background, our contribution asks how these changes in the regulatory environment are reflected at the organizational level of compliance departments. It addresses th作者: 外露 時間: 2025-3-24 01:05
Xueqi Guo,Bo Zhou,Xiongchao Chen,Chi Liu,Nicha C. Dvornekn professional ethics, the patient‘s wishes and behavior, legal norms, and unwritten or formal rules of the organization. Such dilemma situations may lead to delinquency such as the manipulation of data and the alteration of medication to influence the ranking of allocation of a donor organ in patie作者: bronchiole 時間: 2025-3-24 05:31
Jianan Cui,Yutong Xie,Anand A. Joshi,Kuang Gong,Kyungsang Kim,Young-Don Son,Jong-Hoon Kim,Richard Leessure to develop effective compliance management systems (CMS) for preventing, identifying, and prosecuting violations. Against this background, our contribution asks how these changes in the regulatory environment are reflected at the organizational level of compliance departments. It addresses th作者: Lasting 時間: 2025-3-24 10:20 作者: 不斷的變動 時間: 2025-3-24 12:01
Efficient Biomedical Instance Segmentation via?Knowledge Distillationods apply convolutional neural networks to predict pixel embeddings to overcome this problem. However, these methods suffer from heavy computational burdens and massive storage. In this paper, we present the first knowledge distillation method tailored for biomedical instance segmentation to transfe作者: Host142 時間: 2025-3-24 14:54
Tracking by?Weakly-Supervised Learning and?Graph Optimization for?Whole-Embryo , lineagesing that combines weakly-supervised learning from a small set of nuclei center point annotations with an integer linear program (ILP) for optimal cell lineage extraction. Our work specifically addresses the following challenging properties of . embryo recordings: (1) Many cell divisions as compared 作者: 粗魯性質(zhì) 時間: 2025-3-24 22:22
Mask Rearranging Data Augmentation for?3D Mitochondria Segmentationperformance typically rely on extensive training data with high-quality manual annotations, which is time-consuming and labor-intensive. To address this challenge, we propose a novel data augmentation method tailored for 3D mitochondria segmentation. First, we train a Mask2EM network for learning th作者: Substitution 時間: 2025-3-25 01:28 作者: 膽小鬼 時間: 2025-3-25 04:33
Implicit Neural Representations for Generative Modeling of?Living Cell Shapes images. Deep generative models for cell shape synthesis require a?light-weight and flexible representation of the cell shape. However, commonly used voxel-based representations are unsuitable for high-resolution shape synthesis, and polygon meshes have limitations when modeling topology changes suc作者: 獨白 時間: 2025-3-25 07:54 作者: KEGEL 時間: 2025-3-25 14:32
NerveFormer: A Cross-Sample Aggregation Network for?Corneal Nerve Segmentatione-related diseases and systematic diseases. Existing works mainly use convolutional neural networks to improve the segmentation accuracy, while further improvement is needed to mitigate the nerve discontinuity and noise interference. In this paper, we propose a novel corneal nerve segmentation netwo作者: VEST 時間: 2025-3-25 19:08
Domain Adaptive Mitochondria Segmentation via?Enforcing Inter-Section Consistencye and time-consuming to collect. Recently, Unsupervised Domain Adaptation (UDA) has been proposed to avoid annotating on target EM volumes by exploiting annotated source EM volumes. However, existing UDA methods for mitochondria segmentation only address the intra-section gap between source and targ作者: Alveolar-Bone 時間: 2025-3-25 23:48
DeStripe: A Self2Self Spatio-Spectral Graph Neural Network with?Unfolded Hessian for?Stripe Artifactles with decoupled illumination and detection paths. Although the selective excitation scheme of such a microscope provides intrinsic optical sectioning that minimizes out-of-focus fluorescence background and sample photodamage, it is prone to light absorption and scattering effects, which results i作者: cyanosis 時間: 2025-3-26 01:13
End-to-End Cell Recognition by?Point Annotationpervised methods usually estimate probability density maps for cell recognition. However, in dense cell scenarios, their performance can be limited by pre- and post-processing as it is impossible to find a universal parameter setting. In this paper, we introduce an end-to-end framework that applies 作者: ICLE 時間: 2025-3-26 06:28 作者: 偏狂癥 時間: 2025-3-26 09:39 作者: 角斗士 時間: 2025-3-26 13:49
DeepMIF: Deep Learning Based Cell Profiling for?Multispectral Immunofluorescence Images with?Graphicwever, complex makeup of markers in the images hinders the accurate quantification of cell phenotypes. We developed DeepMIF, a new deep learning (DL) based tool with a graphical user interface (GUI) to detect and quantify cell phenotypes on M-IF images, and visualize whole slide image (WSI) and cell作者: 起草 時間: 2025-3-26 20:30 作者: 發(fā)現(xiàn) 時間: 2025-3-26 21:39
MCP-Net: Inter-frame Motion Correction with?Patlak Regularization for?Whole-body Dynamic PETost current deep learning inter-frame motion correction works consider only the image registration problem, ignoring tracer kinetics. We propose an inter-frame Motion Correction framework with Patlak regularization (MCP-Net) to directly optimize the Patlak fitting error and further improve model per作者: 積極詞匯 時間: 2025-3-27 02:15
PET Denoising and?Uncertainty Estimation Based on?NVAE Model Using Quantile Regression Lossme from their uncertainty. As data-driven models, deep learning-based methods are sensitive to imperfect data. Thus, it is important to quantify the uncertainty, especially for positron emission tomography (PET) denoising tasks where the noise is very similar to small tumors. In this paper, we propo作者: BILK 時間: 2025-3-27 06:55 作者: 相符 時間: 2025-3-27 10:31 作者: abysmal 時間: 2025-3-27 16:17
Semi-supervised Learning for?Nerve Segmentation in?Corneal Confocal Microscope Photographyge modeling as a proxy task on unlabeled images. After supervised fine-tuning, self-training is employed to make full use of unlabeled data. Experimental results show that our proposed method is effective and better than the supervised learning using nerve annotations with three-pixel-width dilation.作者: 同義聯(lián)想法 時間: 2025-3-27 20:22 作者: Harridan 時間: 2025-3-28 01:59
https://doi.org/10.1007/978-3-031-16440-8Computer Science; Informatics; Conference Proceedings; Research; Applications作者: 平庸的人或物 時間: 2025-3-28 04:30 作者: 進(jìn)入 時間: 2025-3-28 08:35
978-3-031-16439-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 煤渣 時間: 2025-3-28 10:43
Medical Image Computing and Computer Assisted Intervention – MICCAI 2022978-3-031-16440-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 令人悲傷 時間: 2025-3-28 16:01
0302-9743 reconstruction;.Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; mach978-3-031-16439-2978-3-031-16440-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Arthropathy 時間: 2025-3-28 21:26
Jiayu Chen,Lei Mou,Shaodong Ma,Huazhu Fu,Lijun Guo,Yalin Zheng,Jiong Zhang,Yitian Zhao作者: hysterectomy 時間: 2025-3-29 01:08 作者: 比賽用背帶 時間: 2025-3-29 06:33 作者: photophobia 時間: 2025-3-29 07:54 作者: 頌揚本人 時間: 2025-3-29 12:48
Sunyi Zheng,Jingxiong Li,Zhongyi Shui,Chenglu Zhu,Yunlong Zhang,Pingyi Chen,Lin Yang作者: 雄偉 時間: 2025-3-29 15:49
Medical Image Computing and Computer Assisted Intervention – MICCAI 202225th International C作者: Memorial 時間: 2025-3-29 22:35
An End-to-End Combinatorial Optimization Method for?R-band Chromosome Recognition with?Grouping Guidssignment module (DAM) is designed for flexible and differentiable label assignment. It exploits the aggregated features to infer class probability distributions between all chromosomes in a cell. Experimental results on both normal and numerically abnormal karyotypes confirmed that our method outpe作者: cortisol 時間: 2025-3-30 03:19
Efficient Biomedical Instance Segmentation via?Knowledge Distillationance-level features and instance relationships by the instance graphs built from embeddings of the teacher-student pair, respectively, and (ii) pixel affinity distillation that converts pixel embeddings into pixel affinities and explicitly transfers the structured knowledge of instance boundaries en作者: 強有力 時間: 2025-3-30 05:15
Tracking by?Weakly-Supervised Learning and?Graph Optimization for?Whole-Embryo , lineageshe cell tracking challenge on the . embryo dataset. We report a further extensive quantitative evaluation on two more . datasets. We will make these datasets public to serve as an extended benchmark for future method development. Our results suggest considerable improvements yielded by our method, e作者: 無彈性 時間: 2025-3-30 10:21
Mask Rearranging Data Augmentation for?3D Mitochondria Segmentationnstrate that, as a plug-and-play module, the proposed method boosts existing 3D mitochondria segmentation networks to achieve state-of-the-art performance. Especially, the proposed method brings significant improvements when training data is extremely limited. Code will be available at: ..作者: 蔓藤圖飾 時間: 2025-3-30 14:32
Implicit Neural Representations for Generative Modeling of?Living Cell Shapesd lung cancer cells with growing complex filopodial protrusions. Our results show that shape descriptors of synthetic cells resemble those of real cells, and that our model is able to generate topologically plausible sequences of complex cell shapes in 3D+time.作者: 網(wǎng)絡(luò)添麻煩 時間: 2025-3-30 17:16
Trichomonas Vaginalis Segmentation in?Microscope Imagesng object-level mask labels, object boundaries, and challenging attributes. Besides, we propose a simple yet effective baseline, termed ., to automatically segment Trichomonas from microscopic images, including high-resolution fusion and foreground-background attention modules. Extensive experiments作者: 溝通 時間: 2025-3-30 20:46 作者: Lament 時間: 2025-3-31 04:52
Domain Adaptive Mitochondria Segmentation via?Enforcing Inter-Section Consistencyarget volumes are then aligned via adversarial learning. Meanwhile, guided by the learned inter-section residual, we can generate pseudo labels to supervise the segmentation of adjacent sections inside the target volume, which further enforces inter-section consistency. Extensive experiments demonst作者: 容易懂得 時間: 2025-3-31 05:35
