Automated spinal MRI labelling from reports using a large language model
We propose a general pipeline to automate the extraction of labels from radiology reports using large language models, which we validate on spinal MRI reports. The efficacy of our method is measured on two distinct conditions: spinal cancer and stenosis. Using open-source models, our method surpasse...
Asıl Yazarlar: | Park, RY, Windsor, R, Jamaludin, A, Zisserman, A |
---|---|
Materyal Türü: | Conference item |
Dil: | English |
Baskı/Yayın Bilgisi: |
Springer
2024
|
Benzer Materyaller
-
Automated detection, labelling and radiological grading of clinical spinal MRIs
Yazar:: Windsor, R, ve diğerleri
Baskı/Yayın Bilgisi: (2024) -
Automated detection, labelling and radiological grading of clinical spinal MRIs
Yazar:: Rhydian Windsor, ve diğerleri
Baskı/Yayın Bilgisi: (2024-07-01) -
A convolutional approach to vertebrae detection and labelling in whole spine MRI
Yazar:: Windsor, R, ve diğerleri
Baskı/Yayın Bilgisi: (2020) -
SpineNetV2: Automated detection, labelling and radiological grading of clinical MR scans
Yazar:: Windsor, R, ve diğerleri
Baskı/Yayın Bilgisi: (2022) -
Vision-language modelling for radiological imaging and reports in the low data regime
Yazar:: Windsor, R, ve diğerleri
Baskı/Yayın Bilgisi: (2024)