Zobrazeno 1 - 10
of 4 510
pro vyhledávání: '"Noble, J."'
3D pose estimation from a 2D cross-sectional view enables healthcare professionals to navigate through the 3D space, and such techniques initiate automatic guidance in many image-guided radiology applications. In this work, we investigate how estimat
Externí odkaz:
http://arxiv.org/abs/2408.09931
Concept-based interpretability methods are a popular form of explanation for deep learning models which provide explanations in the form of high-level human interpretable concepts. These methods typically find concept activation vectors (CAVs) using
Externí odkaz:
http://arxiv.org/abs/2408.08652
We present the first automated multimodal summary generation system, MMSummary, for medical imaging video, particularly with a focus on fetal ultrasound analysis. Imitating the examination process performed by a human sonographer, MMSummary is design
Externí odkaz:
http://arxiv.org/abs/2408.03761
Autor:
Sturm, J. A., McClure, M. K., Harsono, D., Bergner, J. B., Dartois, E., Boogert, A. C. A., Cordiner, M. A., Drozdovskaya, M. N., Ioppolo, S., Law, C. J., Lis, D. C., McGuire, B. A., Melnick, G. J., Noble, J. A., Öberg, K. I., Palumbo, M. E., Pendleton, Y. J., Perotti, G., Rocha, W. R. M., Urso, R. G., van Dishoeck, E. F.
Publikováno v:
A&A 689, A92 (2024)
Ice-coated dust grains provide the main reservoir of volatiles that play an important role in planet formation processes and may become incorporated into planetary atmospheres. However, due to observational challenges, the ice abundance distribution
Externí odkaz:
http://arxiv.org/abs/2407.09627
Autor:
Wagner, Felix, Xu, Wentian, Saha, Pramit, Liang, Ziyun, Whitehouse, Daniel, Menon, David, Newcombe, Virginia, Voets, Natalie, Noble, J. Alison, Kamnitsas, Konstantinos
Segmentation models for brain lesions in MRI are commonly developed for a specific disease and trained on data with a predefined set of MRI modalities. Each such model cannot segment the disease using data with a different set of MRI modalities, nor
Externí odkaz:
http://arxiv.org/abs/2406.11636
Unsupervised anomaly segmentation approaches to pathology segmentation train a model on images of healthy subjects, that they define as the 'normal' data distribution. At inference, they aim to segment any pathologies in new images as 'anomalies', as
Externí odkaz:
http://arxiv.org/abs/2406.02422
Recent interpretability methods propose using concept-based explanations to translate the internal representations of deep learning models into a language that humans are familiar with: concepts. This requires understanding which concepts are present
Externí odkaz:
http://arxiv.org/abs/2404.03713
Autor:
Arulanantham, Nicole, McClure, M. K., Pontoppidan, Klaus, Beck, Tracy L., Sturm, J. A., Harsono, D., Boogert, A. C. A., Cordiner, M., Dartois, E., Drozdovskaya, M. N., Espaillat, C., Melnick, G. J., Noble, J. A., Palumbo, M. E., Pendleton, Y. J., Terada, H., van Dishoeck, E. F.
We present JWST MIRI MRS observations of the edge-on protoplanetary disk around the young sub-solar mass star Tau 042021, acquired as part of the Cycle 1 GO program "Mapping Inclined Disk Astrochemical Signatures (MIDAS)." These data resolve the mid-
Externí odkaz:
http://arxiv.org/abs/2402.12256
Autor:
Li, Yiwen, Fu, Yunguan, Gayo, Iani J. M. B., Yang, Qianye, Min, Zhe, Saeed, Shaheer U., Yan, Wen, Wang, Yipei, Noble, J. Alison, Emberton, Mark, Clarkson, Matthew J., Barratt, Dean C., Prisacariu, Victor A., Hu, Yipeng
For training registration networks, weak supervision from segmented corresponding regions-of-interest (ROIs) have been proven effective for (a) supplementing unsupervised methods, and (b) being used independently in registration tasks in which unsupe
Externí odkaz:
http://arxiv.org/abs/2402.10728
Multimodal Federated Learning (MMFL) utilizes multiple modalities in each client to build a more powerful Federated Learning (FL) model than its unimodal counterpart. However, the impact of missing modality in different clients, also called modality
Externí odkaz:
http://arxiv.org/abs/2402.05294