RibAssist 3D：基於CT衍生投影之雙平面肋骨骨折偵測、定位與選擇性3D定位

摘要

肋骨骨折在電腦斷層掃描（CT）上相當常見，且定位過程耗時。本研究探討在兩個正交的CT衍生投影（前後位與側位）中獨立偵測到的骨折，是否能跨視圖配對並三角定位為可靠的三維點，同時將偽輸出率控制在設定範圍內；我們以分階段診斷研究回答此問題。投影幾何具有精確性，且在對應關係正確的前提下，定位結果準確（中位數4.0毫米，88%落在10毫米內，93.6%肋骨層級精確）。在一個封閉的55例 cohort 中，原則上可恢復的骨折佔相當高的比例（61.1%具雙視圖可用性，58.4%的骨折在候選圖中存在正確配對），然而關鍵限制既非幾何亦非定位，而是受信心水準限制的跨視圖對應。一項受控制的「偵測器×對應方法」因子設計顯示，操作增益主要來自側位偵測器品質，而非所測試的匹配方法；重新訓練側位偵測器後，首次產生了非零的受控預算重建結果。在刻意保守的承諾政策下，一項預先指定的封閉測試將601處骨折中的15處提升為正確的三維定位，每例偽點數為0.436（端對端承諾產出率2.50%），且承諾點定位準確（中位數1.49毫米，93%肋骨層級精確）。低產出率源於信心門控的棄權機制，而非幾何或偵測問題：本研究建立了一個可重現的選擇性三維定位框架，並確認跨視圖對應為主要的操作瓶頸。

English

Rib fractures are common and time-consuming to localize on computed tomography (CT). We ask whether fractures detected independently in two orthogonal CT-derived projections (anteroposterior and lateral) can be paired across views and triangulated into reliable 3D points at a controlled rate of false outputs, and we answer it with a staged diagnostic study. The projection geometry is exact, and given correct correspondence, localization is accurate (median 4.0 mm, 88% within 10 mm, 93.6% rib-exact). On a sealed 55-case cohort, a large share of fractures is in principle recoverable (61.1% dual-view availability, and a correct pair present in the candidate graph for 58.4% of fractures), yet the binding limitation is neither geometry nor localization but confidence-limited cross-view correspondence. A controlled detector-by-correspondence factorial attributes the operational gain to lateral-detector quality rather than the tested matching methods; retraining the lateral detector produces the first nonzero controlled-budget reconstructions. Under a deliberately conservative commitment policy, a pre-specified sealed pass promotes 15 of 601 fractures to correct 3D localizations at 0.436 false points per case (2.50% end-to-end commitment yield), and committed points are accurate (median 1.49 mm, 93% rib-exact). The low yield is a consequence of confidence-gated abstention, not of geometry or detection: the study establishes a reproducible framework for selective 3D localization and identifies cross-view correspondence as the dominant operational bottleneck.