Zobrazeno 1 - 10
of 1 466
pro vyhledávání: '"Freiman, P"'
Whole Slide Images (WSIs) are critical for various clinical applications, including histopathological analysis. However, current deep learning approaches in this field predominantly focus on individual tumor types, limiting model generalization and s
Externí odkaz:
http://arxiv.org/abs/2409.11119
Magnetic resonance imaging (MRI) is crucial in diagnosing various abdominal conditions and anomalies. Traditional MRI scans often yield anisotropic data due to technical constraints, resulting in varying resolutions across spatial dimensions, which l
Externí odkaz:
http://arxiv.org/abs/2408.13065
T1 mapping is a valuable quantitative MRI technique for diagnosing diffuse myocardial diseases. Traditional methods, relying on breath-hold sequences and echo triggering, face challenges with patient compliance and arrhythmias, limiting their effecti
Externí odkaz:
http://arxiv.org/abs/2408.11992
Autor:
Hazan, Liam, Focht, Gili, Gavrielov, Naama, Reichart, Roi, Hagopian, Talar, Greer, Mary-Louise C., Kuint, Ruth Cytter, Turner, Dan, Freiman, Moti
Automatic conversion of free-text radiology reports into structured data using Natural Language Processing (NLP) techniques is crucial for analyzing diseases on a large scale. While effective for tasks in widely spoken languages like English, generat
Externí odkaz:
http://arxiv.org/abs/2405.01682
Group polarization, the phenomenon where individuals become more extreme after interacting, has been gaining attention, especially with the rise of social media shaping people's opinions. Recent interest has emerged in formal reasoning about group po
Externí odkaz:
http://arxiv.org/abs/2405.01322
Effective surgical planning for breast cancer hinges on accurately predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Diffusion-weighted MRI (DWI) and machine learning offer a non-invasive approach for early pCR assess
Externí odkaz:
http://arxiv.org/abs/2404.05061
Autor:
Khawaled, Samah, Freiman, Moti
The ability to reconstruct high-quality images from undersampled MRI data is vital in improving MRI temporal resolution and reducing acquisition times. Deep learning methods have been proposed for this task, but the lack of verified methods to quanti
Externí odkaz:
http://arxiv.org/abs/2404.04550
Functional Magnetic Resonance Imaging (fMRI) is vital in neuroscience, enabling investigations into brain disorders, treatment monitoring, and brain function mapping. However, head motion during fMRI scans, occurring between shots of slice acquisitio
Externí odkaz:
http://arxiv.org/abs/2404.04546
Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) but is ineffective for the microsatellite stable (MSS) subtype. There i
Externí odkaz:
http://arxiv.org/abs/2401.16131
Autor:
Zhang, Di, Harmon, Katherine J., Zachman, Michael J., Lu, Ping, Kim, Doyun, Zhang, Zhan, Cucciniello, Nickolas, Markland, Reid, Ssennyimba, Ken William, Zhou, Hua, Cao, Yue, Brahlek, Matthew, Zheng, Hao, Schneider, Matthew M., Mazza, Alessandro R., Hughes, Zach, Somodi, Chase, Freiman, Benjamin, Pooley, Sarah, Kunwar, Sundar, Roy, Pinku, Tu, Qing, McCabe, Rodney J., Chen, Aiping
Developing novel lead-free ferroelectric materials is crucial for next-generation microelectronic technologies that are energy efficient and environment friendly. However, materials discovery and property optimization are typically time-consuming due
Externí odkaz:
http://arxiv.org/abs/2312.17715