计算机科学 ›› 2020, Vol. 47 ›› Issue (10): 200-206.doi: 10.11896/jsjkx.190900073
所属专题: 医学图像
任雪婷1, 赵涓涓1, 强彦1, Saad Abdul RAUF1, 刘继华2
REN Xue-ting1, ZHAO Juan-juan1, QIANG Yan1, Saad Abdul RAUF1, LIU Ji-hua2
摘要: 基因诊断是近年来提高肺癌治愈率的一种新型且有效的方法,但这种方法存在基因检测时间长、费用高、侵入式取样损伤大的问题。文中提出了基于成对学习和图像聚类的无监督学习的肺癌亚型识别方法。首先,采用无监督卷积特征融合网络用于学习肺癌CT图像的深度表示,有效地捕捉被忽略的重要特征信息,并使用包含不同层次抽象信息的最终融合特征来表征肺癌亚型。然后,使用联合成对学习和图像聚类的分类学习框架进行建模,充分利用学习到的特征表示,确保有效的聚类学习,以取得更高的分类精度。最后,利用生存分析和基因分析对肺癌亚型进行多角度验证。在合作医院和TCGA-LUAD数据集上的实验结果表明,该方法通过可靠无创的影像分析和放射成像技术,发现了3种具有不同分子特征的肺癌影像亚型,在降低基因检测问题的同时可有效辅助医师进行精准诊断和个性化治疗,进而提高肺癌患者的治愈生存率。
中图分类号:
[1]SHAO L,SONG Z B,ZHANG Y P,et al.Advances of Molecular Subtype and Targeted Therapy of Lung Cancer[J].Chinese Journal of Lung Cancer,2012,15(9):545-552. [2]YOUNG J D,CAI C,LU X.Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma[J].BMC Bioinformatics,2017,18(S11):381. [3]MAZUROWSKI M A,ZHANG J,GRIMM L J,et al.Radio-genomic Analysis of Breast Cancer:Luminal B Molecular Subtype Is Associated with Enhancement Dynamics at MR Imaging[J].Radiology,2014,273(2):365-372. [4]WILSON R,DEVARAJ A.Radiomics of pulmonary nodules and lung cancer[J].Translational Lung Cancer Research,2017,6(1):86. [5]ZHANG Y,OIKONOMOU A,WONG A,et al.Radiomics-basedprognosis analysis for non-small cell lung cancer[J].Scientific Reports,2017,7:46349. [6]THAWANI R,MCLANE M,BEIG N,et al.Radiomics and radiogenomics in lung cancer:a review for the clinician[J].Lung Cancer,2018,115:34-41. [7]WU J,CUI Y,SUN X L,et al.Unsupervised Clustering ofQuantitative Image Phenotypes Reveals Breast Cancer Subtypes with Distinct Prognoses and Molecular Pathways[J].Clinical Cancer Research,2017,23(13):3334-3342. [8]ITAKURA H,ACHROL A S,MITCHELL L A,et al.Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities[J].Science Translational Medicine,2015,7(303):303ra138-303ra138. [9]YANG J,PARIKH D,BATRA D.Joint unsupervised learning of deep representations and image clusters [C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2016:5147-5156. [10]HAO R,QIANG Y,LIAO X,et al.An automatic detectionmethod for lung nodules based on multi-scale enhancement filters and 3D shape features[J].KSII Transactions on Internet & Information Systems,2019,13(1). [11]WEST L,VIDWANS S J,CAMPBELL N P,et al.A novel classification of lung cancer into molecular subtypes[J].PloS one,2012,7(2):e31906. [12]WU M,MA J.Association Between Imaging Characteristics and Different Molecular Subtypes of Breast Cancer[J].Academic Radiology,2016,24(4):426-434. [13]RATHORE S,AKBARI H,ROZYCKI M,et al.Radiomic MRI signature reveals three distinct subtypes of glioblastoma with different clinical and molecular characteristics,offering prognostic value beyond IDH1[J].Scientific Reports,2018,8(1):5087-5098. [14]LAMBIN P,RIOS-VELAZQUEZ E,LEIJENAAR R,et al.Radiomics:extracting more information from medical images using advanced feature analysis[J].European Journal of Cancer,2012,48(4):441-446. |
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