Accuracy and consistency in RECIST(Response evaluation criteria in solid tumors) measurements are crucial as it directly impacts patient treatment options. Manual RECIST measurement, requiring high expertise & attention, is time-expensive, prone-to-error, operator-subjective. we propose an automated tumor segmentation and RECIST score estimation method that uses MRI image slices as input, delineates the tumor in 3D, identifies the MRI slice with maximum-tumor-burden and then measures the tumor-diameter and RECIST1.1 score for treatment response assessment. Proposed method produced reliable and reproducible automated RECIST score measurements in current bone tumor dataset and might be useful as decision support tool saving manual-effort and reading-time.
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