Curated Multi-Institutional Benchmark Dataset for Validating AI Models for Volumetric Pancreas Segmentation on Contrast-Enhanced CTs
Version 1To rigorously evaluate the robustness and generalizability of an indigenously developed AI model [1] for morphologically normal volumetric pancreas segmentation on portal venous phase CT images, we curated a high-quality external dataset derived from the international multi-institutional AbdomenCT-1K collection [2]. This public dataset comprises 1,062 abdominal CT scans sourced from 12 medical centers and includes five diverse benchmarking subsets: Liver Tumor Segmentation (LiTS), Kidney Tumor S
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To rigorously evaluate the robustness and generalizability of an indigenously developed AI model [1] for morphologically normal volumetric pancreas segmentation on portal venous phase CT images, we curated a high-quality external dataset derived from the international multi-institutional AbdomenCT-1K collection [2]. This public dataset comprises 1,062 abdominal CT scans sourced from 12 medical centers and includes five diverse benchmarking subsets: Liver Tumor Segmentation (LiTS), Kidney Tumor S