Automated deep-learning quantification of nine patellofemoral instability parameters on multislice CT images : development and validation of the GU2Net model
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Aims: Objective and precise measurement of patellar instability (PI) parameters on CT images is essential for accurate diagnosis and treatment planning. However, manual assessment is tedious, time-consuming, and prone to error. T... ...
