3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 3 cited
Can Prompt Learning Benefit Radiology Report Generation?
Jun Wang, Lixing Zhu, Abhir Bhalerao +1
Radiology report generation aims to automatically provide clinically meaningful descriptions of radiology images such as MRI and X-ray. Although great success has been achieved in…
eess.IV2023★ 1 cited
Nuclear Segmentation and Classification: On Color & Compression Generalization
Quoc Dang Vu, Robert Jewsbury, Simon Graham +5
Since the introduction of digital and computational pathology as a field, one of the major problems in the clinical application of algorithms has been the struggle to generalize we…
cs.CV2022
Cross-modal Prototype Driven Network for Radiology Report Generation
Jun Wang, Abhir Bhalerao, Yulan He
Radiology report generation (RRG) aims to describe automatically a radiology image with human-like language and could potentially support the work of radiologists, reducing the bur…