標(biāo)題: Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023; 26th International C Hayit Greenspan,Anant Madabhushi,Russell Tay [打印本頁(yè)] 作者: Strategy 時(shí)間: 2025-3-21 17:26
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023影響因子(影響力)
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023影響因子(影響力)學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023網(wǎng)絡(luò)公開(kāi)度
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023被引頻次
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023被引頻次學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023年度引用
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023年度引用學(xué)科排名
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023讀者反饋
書目名稱Medical Image Computing and Computer Assisted Intervention – MICCAI 2023讀者反饋學(xué)科排名
作者: 甜得發(fā)膩 時(shí)間: 2025-3-21 22:42 作者: entitle 時(shí)間: 2025-3-22 03:59
Towards Novel Class Discovery: A Study in?Novel Skin Lesions Clustering recognize samples from predefined categories, when they are deployed in the clinic, data from new unknown categories are constantly emerging. Therefore, it is crucial to automatically discover and identify new semantic categories from new data. In this paper, we propose a new novel class discovery 作者: 芭蕾舞女演員 時(shí)間: 2025-3-22 07:01 作者: 苦笑 時(shí)間: 2025-3-22 10:52
A Style Transfer-Based Augmentation Framework for?Improving Segmentation and?Classification Performassification performance of deep learning models for ultrasound image analysis. Previous studies have attempted to solve this problem by using style transfer and augmentation techniques, but these methods usually require a large amount of data from multiple sources and source-specific discriminators,作者: SPECT 時(shí)間: 2025-3-22 15:13 作者: 樹(shù)木中 時(shí)間: 2025-3-22 18:12
SegNetr: Rethinking the Local-Global Interactions and Skip Connections in U-Shaped Networks-shaped segmentation networks: 1) mostly focus on designing complex self-attention modules to compensate for the lack of long-term dependence based on convolution operation, which increases the overall number of parameters and computational complexity of the network; 2) simply fuse the features of e作者: 閑逛 時(shí)間: 2025-3-22 21:44 作者: 槍支 時(shí)間: 2025-3-23 05:18
Multi-modality Contrastive Learning for?Sarcopenia Screening from?Hip X-rays and?Clinical Informatiormal muscle strength. Accurate screening for sarcopenia is a key process of clinical diagnosis and therapy. In this work, we propose a novel multi-modality contrastive learning (MM-CL) based method that combines hip X-ray images and clinical parameters for sarcopenia screening. Our method captures t作者: 正式通知 時(shí)間: 2025-3-23 05:43
DiffMIC: Dual-Guidance Diffusion Network for?Medical Image Classificationer vision community. However, while a substantial amount of diffusion-based research has focused on generative tasks, few studies have applied diffusion models to general medical image classification. In this paper, we propose the first diffusion-based model (named DiffMIC) to address general medica作者: grounded 時(shí)間: 2025-3-23 09:46
Whole-Heart Reconstruction with?Explicit Topology Integrated Learning the advancement of medical imaging techniques, computing facilities, and deep learning models, automatically generating whole-heart meshes directly from medical imaging data becomes feasible and shows great potential. Existing works usually employ a point cloud metric, namely the Chamfer distance, 作者: miscreant 時(shí)間: 2025-3-23 15:34
Enhancing Automatic Placenta Analysis Through Distributional Feature Recomposition in?Vision-Languagxamination and report generation, however, are laborious and resource-intensive. Limitations in diagnostic accuracy and model efficiency have impeded previous attempts to automate placenta analysis. This study presents a novel framework for the automatic analysis of placenta images that aims to impr作者: 繼承人 時(shí)間: 2025-3-23 20:10 作者: THROB 時(shí)間: 2025-3-24 01:36
A Semantic-Guided and?Knowledge-Based Generative Framework for?Orthodontic Visual Outcome Previewguided and knowledge-based generative framework to predict the visual outcome of orthodontic treatment from a single frontal photo. The framework involves four steps. Firstly, we perform tooth semantic segmentation and mouth cavity segmentation and extract category-specific teeth contours from front作者: interference 時(shí)間: 2025-3-24 05:00 作者: kindred 時(shí)間: 2025-3-24 07:51
Thinking Like Sonographers: A Deep CNN Model for?Diagnosing Gout from?Musculoskeletal Ultrasound as no prior study on this topic is known. Our exhaustive study of state-of-the-art (SOTA) CNN image classification models for this problem reveals that they often fail to learn the gouty MSKUS features, including the double contour sign, tophus, and snowstorm, which are essential for sonographers’ 作者: Pigeon 時(shí)間: 2025-3-24 14:23
Thyroid Nodule Diagnosis in?Dynamic Contrast-Enhanced Ultrasound via?Microvessel Infiltration Awarension, and may provide more discriminative information than conventional gray ultrasound (US). Thus, CEUS video has vital clinical value in differentiating between malignant and benign thyroid nodules. In particular, the CEUS video can show numerous neovascularisations around the nodule, which consta作者: 詞匯 時(shí)間: 2025-3-24 16:12
Polar Eyeball Shape Net for?3D Posterior Ocular Shape Representationing. However, current shape representations are limited by their low resolution or small field of view, providing insufficient information for surgeons to make accurate decisions. This paper proposes a novel task of reconstructing complete 3D posterior shapes based on small-FOV OCT images and introd作者: Rankle 時(shí)間: 2025-3-24 20:44 作者: OASIS 時(shí)間: 2025-3-25 00:55 作者: 褻瀆 時(shí)間: 2025-3-25 06:27 作者: 同來(lái)核對(duì) 時(shí)間: 2025-3-25 08:01
Lanzhuju Mei,Yu Fang,Zhiming Cui,Ke Deng,Nizhuan Wang,Xuming He,Yiqiang Zhan,Xiang Zhou,Maurizio Ton W?hrend im Westen die etablierte Wohlfahrtsforschung seit Jahren konstante Zusammenh?nge aufzuzeigen wu?te — zwischen objektiven Indikatoren, zum Beispiel Einkommen, Wohnbedingungen, und subjektiven Indikatoren, also etwa Zufriedenheiten, — traten im Osten gerade diesbezüglich Inkongruenzen und Tur作者: 苦澀 時(shí)間: 2025-3-25 14:31 作者: Synchronism 時(shí)間: 2025-3-25 18:23
Xiaohan Xing,Zhen Chen,Zhifan Gao,Yixuan Yuan W?hrend im Westen die etablierte Wohlfahrtsforschung seit Jahren konstante Zusammenh?nge aufzuzeigen wu?te — zwischen objektiven Indikatoren, zum Beispiel Einkommen, Wohnbedingungen, und subjektiven Indikatoren, also etwa Zufriedenheiten, — traten im Osten gerade diesbezüglich Inkongruenzen und Tur作者: LVAD360 時(shí)間: 2025-3-25 22:38 作者: 不成比例 時(shí)間: 2025-3-26 00:25
Yijun Yang,Huazhu Fu,Angelica I. Aviles-Rivero,Carola-Bibiane Sch?nlieb,Lei Zhuie unternimmt erneut einen Akt innovativer Stadtpolitik, für die Heidenheim seit langem vorbildliche Pflanz- und Wirkst?tte ist. Sie erinnert zugleich an den gro?en Sohn der Stadt, den Raumtheoretiker August L?sch. Fast m?chte ich sagen: nie war er so wertvoll wie heute — der Preis für Regionalwisse作者: glucagon 時(shí)間: 2025-3-26 08:06
Huilin Yang,Roger Tam,Xiaoying Tang W?hrend im Westen die etablierte Wohlfahrtsforschung seit Jahren konstante Zusammenh?nge aufzuzeigen wu?te — zwischen objektiven Indikatoren, zum Beispiel Einkommen, Wohnbedingungen, und subjektiven Indikatoren, also etwa Zufriedenheiten, — traten im Osten gerade diesbezüglich Inkongruenzen und Tur作者: Hot-Flash 時(shí)間: 2025-3-26 11:13
Yimu Pan,Tongan Cai,Manas Mehta,Alison D. Gernand,Jeffery A. Goldstein,Leena Mithal,Delia Mwinyelle,ie unternimmt erneut einen Akt innovativer Stadtpolitik, für die Heidenheim seit langem vorbildliche Pflanz- und Wirkst?tte ist. Sie erinnert zugleich an den gro?en Sohn der Stadt, den Raumtheoretiker August L?sch. Fast m?chte ich sagen: nie war er so wertvoll wie heute — der Preis für Regionalwisse作者: Protein 時(shí)間: 2025-3-26 16:16
Heng Li,Haojin Li,Wei Zhao,Huazhu Fu,Xiuyun Su,Yan Hu,Jiang Liu W?hrend im Westen die etablierte Wohlfahrtsforschung seit Jahren konstante Zusammenh?nge aufzuzeigen wu?te — zwischen objektiven Indikatoren, zum Beispiel Einkommen, Wohnbedingungen, und subjektiven Indikatoren, also etwa Zufriedenheiten, — traten im Osten gerade diesbezüglich Inkongruenzen und Tur作者: 胰島素 時(shí)間: 2025-3-26 18:47
Yizhou Chen,Xiaojun Chen W?hrend im Westen die etablierte Wohlfahrtsforschung seit Jahren konstante Zusammenh?nge aufzuzeigen wu?te — zwischen objektiven Indikatoren, zum Beispiel Einkommen, Wohnbedingungen, und subjektiven Indikatoren, also etwa Zufriedenheiten, — traten im Osten gerade diesbezüglich Inkongruenzen und Tur作者: wall-stress 時(shí)間: 2025-3-27 00:57
Yi Shi,Rui-Xiang Li,Wen-Qi Shao,Xin-Cen Duan,Han-Jia Ye,De-Chuan Zhan,Bai-Shen Pan,Bei-Li Wang,Wei G W?hrend im Westen die etablierte Wohlfahrtsforschung seit Jahren konstante Zusammenh?nge aufzuzeigen wu?te — zwischen objektiven Indikatoren, zum Beispiel Einkommen, Wohnbedingungen, und subjektiven Indikatoren, also etwa Zufriedenheiten, — traten im Osten gerade diesbezüglich Inkongruenzen und Tur作者: dry-eye 時(shí)間: 2025-3-27 04:45
Zhi Cao,Weijing Zhang,Keke Chen,Di Zhao,Daoqiang Zhang,Hongen Liao,Fang Chen W?hrend im Westen die etablierte Wohlfahrtsforschung seit Jahren konstante Zusammenh?nge aufzuzeigen wu?te — zwischen objektiven Indikatoren, zum Beispiel Einkommen, Wohnbedingungen, und subjektiven Indikatoren, also etwa Zufriedenheiten, — traten im Osten gerade diesbezüglich Inkongruenzen und Tur作者: 搖擺 時(shí)間: 2025-3-27 06:19 作者: 波動(dòng) 時(shí)間: 2025-3-27 10:38 作者: Defraud 時(shí)間: 2025-3-27 14:20 作者: Frisky 時(shí)間: 2025-3-27 18:26
0302-9743 e 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. ..The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in作者: anticipate 時(shí)間: 2025-3-27 23:35 作者: 填料 時(shí)間: 2025-3-28 04:08 作者: 抱負(fù) 時(shí)間: 2025-3-28 08:37
Multi-modality Contrastive Learning for?Sarcopenia Screening from?Hip X-rays and?Clinical Informatio176 patients to validate the effectiveness of multi-modality based methods. Significant performances with an AUC of 84.64%, ACC of 79.93%, F1 of 74.88%, SEN of 72.06%, SPC of 86.06%, and PRE of 78.44%, show that our method outperforms other single-modality and multi-modality based methods.作者: Minikin 時(shí)間: 2025-3-28 13:53
Thinking Like Sonographers: A Deep CNN Model for?Diagnosing Gout from?Musculoskeletal Ultrasoundes to systematically detect predictions made based on unreasonable/biased reasoning and adjust; (3) How to adjust: Developing a training mechanism to balance gout prediction accuracy and attention reasonability for improved CNNs. The experimental results on clinical MSKUS datasets demonstrate the superiority of our method over several SOTA CNNs.作者: 完成才會(huì)征服 時(shí)間: 2025-3-28 17:45
https://doi.org/10.1007/978-3-031-43987-2applied computing; life and medical sciences; computational biology; computer vision; computing methodol作者: 壯觀的游行 時(shí)間: 2025-3-28 20:38
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/629224.jpg作者: aquatic 時(shí)間: 2025-3-28 23:31 作者: NATTY 時(shí)間: 2025-3-29 06:11
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023978-3-031-43987-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 全部 時(shí)間: 2025-3-29 10:25 作者: 詞匯 時(shí)間: 2025-3-29 15:24
Jann-Ole Henningson,Marion Semmler,Michael D?llinger,Marc Stamminger作者: 不如屎殼郎 時(shí)間: 2025-3-29 17:30 作者: 嚴(yán)峻考驗(yàn) 時(shí)間: 2025-3-29 23:24
Combat Long-Tails in?Medical Classification with?Relation-Aware Consistency and?Virtual Features Comdical image classification in two stages. In the first stage, we devise a Multi-view Relation-aware Consistency (MRC) for representation learning, which provides the training of encoders with unbiased guidance in addition to the imbalanced supervision. In the second stage, to produce an impartial cl作者: 四海為家的人 時(shí)間: 2025-3-30 02:20
Towards Novel Class Discovery: A Study in?Novel Skin Lesions Clusteringd by a self-labeling strategy. Finally, we further refine the pseudo label by aggregating neighborhood information through local sample similarity to improve the clustering performance of the model for unknown categories. We conducted extensive experiments on the dermatology dataset ISIC 2019, and t作者: perjury 時(shí)間: 2025-3-30 07:36
Joint Segmentation and Sub-pixel Localization in Structured Light Laryngoscopyprediction of sub-pixel accurate 2D point locations through weighted least squares in a fully-differentiable manner with negligible computational cost. Lastly, we expand the publicly available Human Laser Endoscopic dataset to also include segmentations of the human vocal folds itself. The source co作者: 掃興 時(shí)間: 2025-3-30 08:41
A Style Transfer-Based Augmentation Framework for?Improving Segmentation and?Classification Performam the style of a training image into various reference styles, which enriches the information from different sources for the network. FeatAug augments the styles at the feature level to compensate for possible style variations, especially for small-size datasets with limited styles. MaskAug leverage作者: 褲子 時(shí)間: 2025-3-30 13:47 作者: 的事物 時(shí)間: 2025-3-30 19:18
SegNetr: Rethinking the Local-Global Interactions and Skip Connections in U-Shaped Networksial location information of encoder features and achieve accurate fusion with the decoder features. We validate the effectiveness of SegNetr on four mainstream medical image segmentation datasets, with 59% and 76% fewer parameters and GFLOPs than vanilla U-Net, while achieving segmentation performan作者: 撕裂皮肉 時(shí)間: 2025-3-30 21:25 作者: rectocele 時(shí)間: 2025-3-31 01:59 作者: 廚師 時(shí)間: 2025-3-31 07:39 作者: LEVER 時(shí)間: 2025-3-31 10:43
Frequency-Mixed Single-Source Domain Generalization for?Medical Image Segmentation constructed in the domain augmentation to learn robust context-aware representations for the segmentation task. Experimental results on five datasets of three modalities demonstrate the effectiveness of the proposed algorithm. FreeSDG outperforms state-of-the-art methods and significantly improves 作者: 簡(jiǎn)略 時(shí)間: 2025-3-31 15:09
