Zobrazeno 1 - 10
of 309
pro vyhledávání: '"Dowling, Jason A"'
Autor:
Xin, Bowen, Young, Tony, Wainwright, Claire E, Blake, Tamara, Lebrat, Leo, Gaass, Thomas, Benkert, Thomas, Stemmer, Alto, Coman, David, Dowling, Jason
Medical image synthesis generates additional imaging modalities that are costly, invasive or harmful to acquire, which helps to facilitate the clinical workflow. When training pairs are substantially misaligned (e.g., lung MRI-CT pairs with respirato
Externí odkaz:
http://arxiv.org/abs/2408.09432
The Shared Task on Large-Scale Radiology Report Generation (RRG24) aims to expedite the development of assistive systems for interpreting and reporting on chest X-ray (CXR) images. This task challenges participants to develop models that generate the
Externí odkaz:
http://arxiv.org/abs/2408.03500
Clinical documentation is an important aspect of clinicians' daily work and often demands a significant amount of time. The BioNLP 2024 Shared Task on Streamlining Discharge Documentation (Discharge Me!) aims to alleviate this documentation burden by
Externí odkaz:
http://arxiv.org/abs/2407.02723
This study investigates the integration of diverse patient data sources into multimodal language models for automated chest X-ray (CXR) report generation. Traditionally, CXR report generation relies solely on CXR images and limited radiology data, ov
Externí odkaz:
http://arxiv.org/abs/2406.13181
Multiparametric magnetic resonance imaging (mpMRI) is a key tool for assessing breast cancer progression. Although deep learning has been applied to automate tumor segmentation in breast MRI, the effect of sequence combinations in mpMRI remains under
Externí odkaz:
http://arxiv.org/abs/2406.07813
Radiologists face high burnout rates, partially due to the increasing volume of Chest X-rays (CXRs) requiring interpretation and reporting. Automated CXR report generation holds promise for reducing this burden and improving patient care. While curre
Externí odkaz:
http://arxiv.org/abs/2307.09758
Autor:
Chlap, Phillip, Min, Hang, Dowling, Jason, Field, Matthew, Cloak, Kirrily, Leong, Trevor, Lee, Mark, Chu, Julie, Tan, Jennifer, Tran, Phillip, Kron, Tomas, Sidhom, Mark, Wiltshire, Kirsty, Keats, Sarah, Kneebone, Andrew, Haworth, Annette, Ebert, Martin A., Vinod, Shalini K., Holloway, Lois
Publikováno v:
In Computerized Medical Imaging and Graphics September 2024 116
Automatically generating a report from a patient's Chest X-Rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report generators -- which are predominantly encoder-to-decoder models -- la
Externí odkaz:
http://arxiv.org/abs/2201.09405
Autor:
Dai, Wei, Woo, Boyeong, Liu, Siyu, Marques, Matthew, Engstrom, Craig B., Greer, Peter B., Crozier, Stuart, Dowling, Jason A., Chandra, Shekhar S.
Direct automatic segmentation of objects from 3D medical imaging, such as magnetic resonance (MR) imaging, is challenging as it often involves accurately identifying a number of individual objects with complex geometries within a large volume under i
Externí odkaz:
http://arxiv.org/abs/2109.05443
Autor:
Texier, Blanche, Hémon, Cédric, Queffélec, Adélie, Dowling, Jason, Bessieres, Igor, Greer, Peter, Acosta, Oscar, Boue-Rafle, Adrien, de Crevoisier, Renaud, Lafond, Caroline, Castelli, Joël, Barateau, Anaïs, Nunes, Jean-Claude
Publikováno v:
In Physics and Imaging in Radiation Oncology July 2024 31