Development and clinical application of an ultrasound-based deep learning model for preoperative staging of colorectal cancer

Figure 1 Overall study design. The study consisted of four phases: (1) Data collection from development cohort (n = 680) and independent test cohort (n = 170); (2) Image preprocessing including tumor annotation and quality assessment; (3) Construction of the dual-path context-aware fusion network for T and N staging; and (4) Model evaluation using cross-validation and independent test set. FPN: Feature pyramid networks; AUC: Area under the curve; AI: Artificial intelligence.