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由于醫(yī)學(xué)圖像數(shù)據(jù)爆炸式增長，傳統(tǒng)依靠醫(yī)生人工對醫(yī)學(xué)圖像進(jìn)行分析診斷，醫(yī)生易出現(xiàn)疲勞，不僅工作效率低下，工作量大，還容易產(chǎn)生誤診、漏診。隨著人工智能（artificial intelligence，AI）技術(shù)的發(fā)展與應(yīng)用，機(jī)器學(xué)習(xí)（machine learning，ML），尤其是深度學(xué)習(xí)（deep learning，DL）在醫(yī)學(xué)圖像分析領(lǐng)域發(fā)揮著越來越重要的作用。為了進(jìn)一步了解DL在醫(yī)學(xué)圖像自動分割和分類識別中的研究，本文對DL及其在醫(yī)學(xué)圖像分析領(lǐng)域的研究進(jìn)展進(jìn)行綜述。為DL在解決醫(yī)學(xué)圖像分析診斷方面提供有益參考。

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