標(biāo)題: Titlebook: Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data ; 6th Joint Internatio M. Jorge Cardoso [打印本頁(yè)] 作者: counterfeit 時(shí)間: 2025-3-21 18:07
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 影響因子(影響力)
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 影響因子(影響力)學(xué)科排名
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 被引頻次
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 被引頻次學(xué)科排名
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 年度引用
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 年度引用學(xué)科排名
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 讀者反饋
書(shū)目名稱Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 讀者反饋學(xué)科排名
作者: 劇毒 時(shí)間: 2025-3-21 21:29
Vascular Segmentation in TOF MRA Images of the Brain Using a Deep Convolutional Neural Networkally analyzed using the trained CNN by considering the intensity values of neighboring voxels that belong to its patch. Experiments were performed with TOF MRA images of five healthy subjects, using varying numbers of images to train the CNN. Cross validations revealed that the proposed framework is作者: Evolve 時(shí)間: 2025-3-22 01:59
VOIDD: Automatic Vessel-of-Intervention Dynamic Detection in PCI Procedurestion and correct identification of the vessel navigated during the procedure. On a dataset of 2213 images from 8 sequences of 4 patients, VOIDD identifies vessel-of-intervention with accuracy in the range of?. or above and absence of tip with accuracy in range of?. or above depending on the test cas作者: 格言 時(shí)間: 2025-3-22 08:31
Towards an Efficient Way of Building Annotated Medical Image Collections for Big Data Studies assigning tasks such as labeling and contouring for big data medical imaging studies. This is a web-based platform and provides the tooling for both researchers and annotators, all within a simple dynamic user interface. Our annotation platform also streamlines the process of iteratively training a作者: QUAIL 時(shí)間: 2025-3-22 09:14 作者: 工作 時(shí)間: 2025-3-22 16:38 作者: Crater 時(shí)間: 2025-3-22 20:19 作者: 小樣他閑聊 時(shí)間: 2025-3-22 23:31 作者: 散布 時(shí)間: 2025-3-23 02:59 作者: 好忠告人 時(shí)間: 2025-3-23 06:00
Yaniv Gur,Mehdi Moradi,Hakan Bulu,Yufan Guo,Colin Compas,Tanveer Syeda-Mahmoodengineering tools for improving pattern control and array efficiency including lattice selection, subarrray technology and pattern synthesis. Equations and figurers quantify the phenomena being described and provide the reader with the tools to tradeoff various performance features. The discussions 作者: spondylosis 時(shí)間: 2025-3-23 12:56
Laurent Lejeune,Mario Christoudias,Raphael Sznitmanengineering tools for improving pattern control and array efficiency including lattice selection, subarrray technology and pattern synthesis. Equations and figurers quantify the phenomena being described and provide the reader with the tools to tradeoff various performance features. The discussions 作者: RALES 時(shí)間: 2025-3-23 14:21 作者: 跟隨 時(shí)間: 2025-3-23 18:08
Mian Huang,Ghassan Hamarnehfacturing imperfections and design limitations;.Enables readers to understand the firm theoretical foundation of antenna gain ?even when they must start from well-known formulations rather than first principles978-3-030-04678-1作者: 細(xì)微差別 時(shí)間: 2025-3-24 01:37
Luis Alvarez,Esther González,Julio Esclarín,Luis Gomez,Miguel Alemán-Flores,Agustín Trujillo,Carmelo作者: 不能和解 時(shí)間: 2025-3-24 04:24
Simone Balocco,Francesco Ciompi,Juan Rigla,Xavier Carrillo,Josepa Mauri,Petia Radeva作者: bonnet 時(shí)間: 2025-3-24 09:21 作者: 沒(méi)花的是打擾 時(shí)間: 2025-3-24 13:23 作者: CUMB 時(shí)間: 2025-3-24 18:54
Nicholas Heller,Panagiotis Stanitsas,Vassilios Morellas,Nikolaos Papanikolopoulos作者: capsaicin 時(shí)間: 2025-3-24 21:26
Sebastian Otálora,Oscar Perdomo,Fabio González,Henning Müller作者: Lethargic 時(shí)間: 2025-3-24 23:51
Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data 6th Joint Internatio作者: 盟軍 時(shí)間: 2025-3-25 05:22
Joseph G. Jacobs,Gabriel J. Brostow,Alex Freeman,Daniel C. Alexander,Eleftheria Panagiotaki. Equations and figurers quantify the phenomena being described and provide the reader with the tools to tradeoff various performance features. The discussions 978-3-031-00406-3978-3-031-01534-2Series ISSN 1932-6076 Series E-ISSN 1932-6084 作者: FLASK 時(shí)間: 2025-3-25 08:19
Alison Q. O’Neil,John T. Murchison,Edwin J. R. van Beek,Keith A. Goatman. Equations and figurers quantify the phenomena being described and provide the reader with the tools to tradeoff various performance features. The discussions 978-3-031-00406-3978-3-031-01534-2Series ISSN 1932-6076 Series E-ISSN 1932-6084 作者: 幼兒 時(shí)間: 2025-3-25 14:44
0302-9743 and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2017, and the Second International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2017, held in conjunction with the 20th International Conference on Medical Imaging and C作者: 大暴雨 時(shí)間: 2025-3-25 19:22 作者: 圓桶 時(shí)間: 2025-3-25 22:54 作者: 外表讀作 時(shí)間: 2025-3-26 03:33
DCNN-Based Automatic Segmentation and Quantification of Aortic Thrombus Volume: Influence of the Trabus volume assessment, starting from its segmentation based on a Deep Convolutional Neural Network (DCNN) both pre-operatively and post-operatively. The aim is to investigate several training approaches to evaluate their influence in the thrombus volume characterization.作者: LUDE 時(shí)間: 2025-3-26 06:12
Expected Exponential Loss for Gaze-Based Video and Volume Ground Truth Annotationmi-supervised setting using a novel Expected Exponential loss function. We show that our framework provides superior performances on a wide range of medical image settings compared to existing strategies and that our method can be combined with current crowd-sourcing paradigms as well.作者: subordinate 時(shí)間: 2025-3-26 10:56 作者: Inveterate 時(shí)間: 2025-3-26 15:51 作者: G-spot 時(shí)間: 2025-3-26 20:08 作者: 輕信 時(shí)間: 2025-3-26 22:35
Conference proceedings 2017arefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing..作者: IST 時(shí)間: 2025-3-27 04:26 作者: 混沌 時(shí)間: 2025-3-27 05:20
Exploring the Similarity of Medical Imaging Classification Problemsing to their origin with 89.3% accuracy. These findings, together with the observations of recent trends in machine learning, suggest that meta-learning could be a valuable tool for the medical imaging community.作者: 懸崖 時(shí)間: 2025-3-27 12:45
Real Data Augmentation for Medical Image Classificationling time. In our experiments, Unified LF&SM performed best, selecting a high percentage of relevant images in its recommendation and achieving the best classification accuracy. It is easily extendable to other medical image classification problems.作者: indigenous 時(shí)間: 2025-3-27 15:33 作者: 經(jīng)典 時(shí)間: 2025-3-27 18:49
Crowdsourcing Labels for Pathological Patterns in CT Lung Scans: Can Non-experts Contribute Expert-Qle observer, matching the reference repeatability for 5 of 7 patterns. In conclusion, crowdsourcing from non-experts yields acceptable quality ground truth, given sufficient expert task supervision and a sufficient number of observers per scan.作者: 名字 時(shí)間: 2025-3-28 01:48 作者: 悶熱 時(shí)間: 2025-3-28 04:19
A Web-Based Platform for Distributed Annotation of Computerized Tomography Scansevaluate the relationship between the size of the harvested regions and the quality of the annotations. Finally, we present additional functionality of the developed platform for the closer examination of 3D point clouds for kidney cancer.作者: surmount 時(shí)間: 2025-3-28 06:52 作者: 能量守恒 時(shí)間: 2025-3-28 13:39
Intra-coronary Stent Localization in Intravascular Ultrasound Sequences, A Preliminary Studyound (IVUS) is a catheter-based imaging technique generally used for assessing the correct placement of the stent. All the approaches proposed so far for the stent analysis only focused on the struts detection, while this paper proposes a novel approach to detect the boundaries and the position of t作者: sacrum 時(shí)間: 2025-3-28 14:47 作者: Irrepressible 時(shí)間: 2025-3-28 19:06
DCNN-Based Automatic Segmentation and Quantification of Aortic Thrombus Volume: Influence of the Traential during follow-up?to evaluate the progress of the patient along time, comparing it to the pre-operative situation, and to detect complications. In this context, accurate assessment of the aneurysm or thrombus volume pre- and post-operatively is required. However, a quantifiable and trustworthy作者: 英寸 時(shí)間: 2025-3-29 02:29 作者: STANT 時(shí)間: 2025-3-29 04:46 作者: SIT 時(shí)間: 2025-3-29 09:56 作者: 分解 時(shí)間: 2025-3-29 13:41
Real Data Augmentation for Medical Image Classification only appear in a very small portion of the entire dataset. Nowadays, large collections of medical images are readily available. However, it is costly and may not even be feasible for medical experts to manually comb through a huge unlabeled dataset to obtain enough representative examples of the ra作者: 合乎習(xí)俗 時(shí)間: 2025-3-29 18:22 作者: Anticonvulsants 時(shí)間: 2025-3-29 23:40 作者: 助記 時(shí)間: 2025-3-30 02:36 作者: 容易生皺紋 時(shí)間: 2025-3-30 07:01
Expected Exponential Loss for Gaze-Based Video and Volume Ground Truth Annotationobject segmentation, pixel-wise annotations are extremely expensive to collect, especially in video and 3D volumes. To reduce this annotation burden, we propose a novel framework to allow annotators to simply observe the object to segment and record where they have looked at with a $200 eye gaze tra作者: Acclaim 時(shí)間: 2025-3-30 08:32
SwifTree: Interactive Extraction of 3D Trees Supporting Gaming and Crowdsourcingese tree-like structures from 3D data remains an open problem due to their complex branching patterns, geometrical diversity, and pathology. On the other hand, it is challenging to design intuitive interactive methods that are practical to use in 3D for trees with tens or hundreds of branches. We pr作者: Definitive 時(shí)間: 2025-3-30 15:56 作者: Semblance 時(shí)間: 2025-3-30 19:14
A Web-Based Platform for Distributed Annotation of Computerized Tomography Scansperts with providing faster diagnoses. The success of CAD systems heavily relies on the availability of high-quality annotated data. Towards supporting the annotation process among teams of medical experts, we present a web-based platform developed for distributed annotation of medical images. We ca作者: candle 時(shí)間: 2025-3-30 21:41
Training Deep Convolutional Neural Networks with Active Learning for Exudate Classification in Eye Folutional networks (CNN) has been successfully used as an automatic detection tool to support the grading of diabetic retinopathy and macular edema. Nevertheless, the manual annotation of exudates in eye fundus images used to classify the grade of the DR is very time consuming and repetitive for cli作者: forecast 時(shí)間: 2025-3-31 02:59 作者: 可轉(zhuǎn)變 時(shí)間: 2025-3-31 06:45
Ketan Bacchuwar,Jean Cousty,Régis Vaillant,Laurent Najman method, are performed to investigate both electronic and magnetic properties of the Fe.O.. Polarized spin and spin–orbit coupling are included in calculations within the framework of the antiferromagnetic state between two adjacent Fe plans. The antiferromagnetic and ferromagnetic energies of Fe.O.作者: 沒(méi)花的是打擾 時(shí)間: 2025-3-31 10:48 作者: 灌輸 時(shí)間: 2025-3-31 16:21
