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目的 探討基于卷積神經(jīng)網(wǎng)絡(luò)的肝臟組織切片圖像正常和病變性分類方法的可行性及應(yīng)用價(jià)值。方法 使用一種能夠自動(dòng)學(xué)習(xí)圖像特征并分類的方法，先利用原始的Inception V3 模型對(duì)肝臟組織切片數(shù)據(jù)集上進(jìn)行訓(xùn)練，然后在原始模型的基礎(chǔ)上通過微調(diào)得到改進(jìn)的Inception V3模型，最后用改進(jìn)的模型來實(shí)現(xiàn)肝臟組織切片圖像正常和病變性兩種類型的分類。結(jié)果 改進(jìn)后的Inception V3模型對(duì)肝臟切片圖像的分類結(jié)果較佳，平均分類準(zhǔn)確率達(dá)到99.2%。結(jié)論 卷積神經(jīng)網(wǎng)絡(luò)的肝臟組織切片圖像正常和病變性分類方法可行、合理，改進(jìn)的Inception V3模型的分類效果較好。

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