標(biāo)題: Titlebook: Interpretable and Annotation-Efficient Learning for Medical Image Computing; Third International Jaime Cardoso,Hien Van Nguyen,Samaneh Abb [打印本頁] 作者: GLAZE 時(shí)間: 2025-3-21 17:20
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing影響因子(影響力)
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing影響因子(影響力)學(xué)科排名
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing網(wǎng)絡(luò)公開度
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing被引頻次
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing被引頻次學(xué)科排名
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing年度引用
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing年度引用學(xué)科排名
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing讀者反饋
書目名稱Interpretable and Annotation-Efficient Learning for Medical Image Computing讀者反饋學(xué)科排名
作者: 滑動(dòng) 時(shí)間: 2025-3-21 22:32 作者: Arroyo 時(shí)間: 2025-3-22 01:33
Conference proceedings 2020 Computing, iMIMIC 2020, the Second International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020, and the 5th International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, LABELS 2020, held in conjunction with the 23rd Internatio作者: exercise 時(shí)間: 2025-3-22 06:45
Projective Latent Interventions for Understanding and Fine-Tuning Classifierss allow domain experts to control the latent decision space in an intuitive way in order to better match their expectations. For instance, the performance for specific pairs of classes can be enhanced by manually separating the class clusters in the embedding. We evaluate our technique on a real-world scenario in fetal ultrasound imaging.作者: 群居男女 時(shí)間: 2025-3-22 09:02 作者: ULCER 時(shí)間: 2025-3-22 14:28 作者: 大廳 時(shí)間: 2025-3-22 18:42 作者: 墻壁 時(shí)間: 2025-3-22 21:40
Eren Bora Yilmaz,Alexander Oliver Mader,Tobias Fricke,Jaime Pe?a,Claus-Christian Glüer,Carsten Meyerh Unl?slichkeit in Wasser und Aussehen lebhaft an das Wismuthydrat erinnern. Aus der Stellung des Arsens im periodischen System über dem Antimon ergibt sich ohne weiteres, da? die Oxyde und Sulfide des Arsens st?rker sauren Charakter haben als die gleichen Verbindungen des Antimons. Die Arsenoxyde u作者: 職業(yè)拳擊手 時(shí)間: 2025-3-23 05:10 作者: 急急忙忙 時(shí)間: 2025-3-23 09:31 作者: 摻和 時(shí)間: 2025-3-23 10:24 作者: 匯總 時(shí)間: 2025-3-23 16:34 作者: Lymphocyte 時(shí)間: 2025-3-23 20:09
Aniket Joshi,Gaurav Mishra,Jayanthi Sivaswamy Korea eine Kolonie Japans war, wurde die Bezeichnung Joseon beibehalten. In den Jahren 1945 bis 1948 war der Süden Koreas von amerikanischen Truppen besetzt, w?hrend der Norden sowjetisches Einflussgebiet wurde. 1948 wurde Korea in die südkoreanische Republik und die nordkoreanische Volksrepublik g作者: 四目在模仿 時(shí)間: 2025-3-24 01:07 作者: semiskilled 時(shí)間: 2025-3-24 05:03
Angshuman Paul,Thomas C. Shen,Niranjan Balachandar,Yuxing Tang,Yifan Peng,Zhiyong Lu,Ronald M. Summe der typischen Inhalte der ersten Studienphase dem ?Was" das ?Wie" gleichberechtigt zur Seite stellt. . Der Text zielt auf ein Verst?ndnis der Mathematik als Methode ab, erkl?rt die mathematische Sprache, allgemeine Prinzipien und Konventionen und macht das oft Implizite und Unausgesprochene offizie作者: 草本植物 時(shí)間: 2025-3-24 09:46
Chongchong Song,Baochun He,Hongyu Chen,Shuangfu Jia,Xiaoxia Chen,Fucang Jia der typischen Inhalte der ersten Studienphase dem ?Was" das ?Wie" gleichberechtigt zur Seite stellt. . Der Text zielt auf ein Verst?ndnis der Mathematik als Methode ab, erkl?rt die mathematische Sprache, allgemeine Prinzipien und Konventionen und macht das oft Implizite und Unausgesprochene offizie作者: defray 時(shí)間: 2025-3-24 14:23
Assessing Attribution Maps for Explaining CNN-Based Vertebral Fracture Classifiershms. Quantitative and visual tests were conducted to evaluate the meaningfulness of the explanations (sanity checks). The explanations were found to depend on the model architecture, the realization of the parameters, and the precise position of the target object of interest.作者: Hemoptysis 時(shí)間: 2025-3-24 16:12
Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical Imaging of histopathology images. These are relevant applications to enlarge the existing medical datasets with open-access images as those of PubMed Central. All experiments are performed on publicly available data and the code is shared on GitHub.作者: ordain 時(shí)間: 2025-3-24 22:01
Improving the Performance and Explainability of Mammogram Classifiers with Local Annotationsng data. We observe that training with only 20–40% of the local annotations is sufficient to achieve improved performance and explainability comparable to a classifier trained with the entire set of local annotations.作者: 準(zhǔn)則 時(shí)間: 2025-3-25 02:31
Improving Interpretability for Computer-Aided Diagnosis Tools on Whole Slide Imaging with Multiple Ication architectures on Camelyon-16 WSI dataset, highlighting discriminative features learned, and validating our approach with pathologists, we propose a novel manner of computing interpretability slide-level heat-maps, based on the extracted features, that improves tile-level classification perfor作者: 偽造 時(shí)間: 2025-3-25 03:57
Explainable Disease Classification via Weakly-Supervised Segmentationmacular edema (DME) from OCT slices. Results of testing on a large public dataset show that with just a third of images with roughly segmented fluid filled regions, the classification accuracy is on par with state of the art methods while providing a good explanation in the form of anatomically accu作者: 胡言亂語 時(shí)間: 2025-3-25 08:34 作者: outrage 時(shí)間: 2025-3-25 11:52
COMe-SEE: Cross-modality Semantic Embedding Ensemble for Generalized Zero-Shot Diagnosis of Chest Ra. Experiments on two publicly available datasets show that the proposed model can be trained using one dataset and still be applied to data from another source for zero-shot diagnosis of chest x-rays.作者: 使虛弱 時(shí)間: 2025-3-25 16:46 作者: 老人病學(xué) 時(shí)間: 2025-3-25 23:02
Uncertainty Estimation in Medical Image Localization: Towards Robust Anterior Thalamus Targeting forst-Time Augmentation (TTA) on the second-stage localization network. Moreover, we propose a novel uncertainty estimation metric called maximum activation dispersion (MAD) to estimate the image-wise uncertainty for localization tasks. Our results show that the proposed method achieved more robust loc作者: Herpetologist 時(shí)間: 2025-3-26 01:25 作者: Systemic 時(shí)間: 2025-3-26 05:20 作者: PRO 時(shí)間: 2025-3-26 11:01 作者: 火花 時(shí)間: 2025-3-26 14:22
0302-9743 ices in medical image learning with label scarcity and data imperfection. The LABELS papers present a variety of approaches for dealing with a limited number of978-3-030-61165-1978-3-030-61166-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: ALIEN 時(shí)間: 2025-3-26 18:36
Colin B. Hansen,Vishwesh Nath,Riqiang Gao,Camilo Bermudez,Yuankai Huo,Kim L. Sandler,Pierre P. Massiite stellt. . Der Text zielt auf ein Verst?ndnis der Mathematik als Methode ab, erkl?rt die mathematische Sprache, allgemeine Prinzipien und Konventionen und macht das oft Implizite und Unausgesprochene offizie978-3-662-56805-7978-3-662-56806-4作者: BRUNT 時(shí)間: 2025-3-27 00:57
Han Liu,Can Cui,Dario J. Englot,Benoit M. Dawantite stellt. . Der Text zielt auf ein Verst?ndnis der Mathematik als Methode ab, erkl?rt die mathematische Sprache, allgemeine Prinzipien und Konventionen und macht das oft Implizite und Unausgesprochene offizie978-3-662-56805-7978-3-662-56806-4作者: stroke 時(shí)間: 2025-3-27 03:51 作者: 閑聊 時(shí)間: 2025-3-27 06:07 作者: 脫離 時(shí)間: 2025-3-27 11:07 作者: Pelago 時(shí)間: 2025-3-27 16:17 作者: Trabeculoplasty 時(shí)間: 2025-3-27 21:17 作者: Nucleate 時(shí)間: 2025-3-28 00:13
Maximilian M?ller,Matthias Kohl,Stefan Braunewell,Florian Kofler,Benedikt Wiestler,Jan S. Kirschke,Balten: grundlegende Ideen und Schreibweisen, Aussagenlogik, naive Mengenlehre, algebraische Strukturen, Zahlenmengen und analytische Geometrie. .978-3-642-01729-2Series ISSN 0937-7433 Series E-ISSN 2512-5214 作者: JECT 時(shí)間: 2025-3-28 03:22
Jing Zhang,Caroline Petitjean,Florian Yger,Samia Ainouzalten: grundlegende Ideen und Schreibweisen, Aussagenlogik, naive Mengenlehre, algebraische Strukturen, Zahlenmengen und analytische Geometrie. .978-3-642-01729-2Series ISSN 0937-7433 Series E-ISSN 2512-5214 作者: Vaginismus 時(shí)間: 2025-3-28 08:03
nhalten: grundlegende Ideen und Schreibweisen, Aussagenlogik, naive Mengenlehre, algebraische Strukturen, Zahlenmengen und analytische Geometrie. .978-3-642-28646-9Series ISSN 0937-7433 Series E-ISSN 2512-5214 作者: 你敢命令 時(shí)間: 2025-3-28 11:23 作者: 諷刺 時(shí)間: 2025-3-28 15:10
978-3-030-61165-1Springer Nature Switzerland AG 2020作者: 不整齊 時(shí)間: 2025-3-28 19:44
Interpretable and Annotation-Efficient Learning for Medical Image Computing978-3-030-61166-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 旁觀者 時(shí)間: 2025-3-28 23:23 作者: 傳染 時(shí)間: 2025-3-29 05:27 作者: sacrum 時(shí)間: 2025-3-29 09:30 作者: anaerobic 時(shí)間: 2025-3-29 12:09 作者: Presbycusis 時(shí)間: 2025-3-29 15:37
Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical ImagingWith feature transfer being a common practice, scale-invariant features implicitly learned from pretraining on ImageNet tend to be preferred over scale-covariant features. The pruning strategy in this paper proposes a way to maintain scale covariance in the transferred features. Deep learning interp作者: Halfhearted 時(shí)間: 2025-3-29 23:48 作者: 含糊其辭 時(shí)間: 2025-3-30 00:06
Improving Interpretability for Computer-Aided Diagnosis Tools on Whole Slide Imaging with Multiple Ievel, interpretability (highlight how and what a trained model learned and why it makes a specific decision) is the next important challenge that deep learning methods need to answer to be fully integrated in the medical field. In this paper, we address the question of interpretability in the contex作者: DRILL 時(shí)間: 2025-3-30 07:53
Explainable Disease Classification via Weakly-Supervised Segmentationhese systems achieve high to very high accuracy in specific disease detection for which they are trained but lack in terms of an explanation for the provided decision/classification result. The activation maps which correspond to decisions do not correlate well with regions of interest for specific 作者: lanugo 時(shí)間: 2025-3-30 12:08 作者: 作繭自縛 時(shí)間: 2025-3-30 13:07 作者: ferment 時(shí)間: 2025-3-30 18:27
Recovering the Imperfect: Cell Segmentation in the Presence of Dynamically Localized Proteinssible only temporarily, existing frame-by-frame methods fail. In this paper, we provide a solution to segmentation of imperfect data through time based on temporal propagation and uncertainty estimation. We integrate uncertainty estimation into Mask R-CNN network and propagate motion-corrected segme作者: OTHER 時(shí)間: 2025-3-30 22:51 作者: adumbrate 時(shí)間: 2025-3-31 04:42 作者: 他日關(guān)稅重重 時(shí)間: 2025-3-31 08:13
Semi-supervised Machine Learning with MixMatch and Equivalence Classesot been well translated to medical imaging. Of particular interest, the MixMatch method achieves significant performance improvement over popular semi-supervised learning methods with scarce labels in the CIFAR-10 dataset. In a complementary approach, Nullspace Tuning on equivalence classes offers t作者: 背叛者 時(shí)間: 2025-3-31 10:56
Non-contrast CT Liver Segmentation Using CycleGAN Data Augmentation from Contrast Enhanced CTdaries and scarce supervised training data than contrast-enhanced CT (CTce) segmentation. To alleviate manual labelling work of radiologists, we generate training samples for 3D U-Net segmentation network by transforming the existing CTce liver segmentation dataset to the non-contrast CT styled volu作者: 欲望 時(shí)間: 2025-3-31 14:51
Uncertainty Estimation in Medical Image Localization: Towards Robust Anterior Thalamus Targeting for, but these are known to lack robustness when anatomic differences between atlases and subjects are large. To improve the localization robustness, we propose a novel two-stage deep learning (DL) framework, where the first stage identifies and crops the thalamus regions from the whole brain MRI and t作者: 財(cái)主 時(shí)間: 2025-3-31 20:43
A Case Study of Transfer of?Lesion-Knowledgeng with the acknowledged ability of neural-network methods to analyse image data, would suggest that accurate models for lesions can now be constructed by a deep neural network. However an important difficulty arises from the lack of annotated images from various parts of the body. Our proposed appr作者: TAP 時(shí)間: 2025-4-1 01:35 作者: 工作 時(shí)間: 2025-4-1 03:54
Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-domain Liver Segmentationer, the well-trained models often fail in the target domain due to the domain shift. Unsupervised domain adaptation aims to improve network performance when applying robust models trained on medical images from source domains to a new target domain. In this work, we present an approach based on the
