Automatic contouring system for cervical cancer using convolutional neural networks.
Automatic contouring system for cervical cancer using convolutional neural networks.
复制标题
DOI：
10.1002/mp.14467
复制
发表时间：
2020-11
期刊：
影响因子：
3.8
通讯作者：
Court LE
中科院分区：
文献类型：
--
作者：
Rhee DJ;Jhingran A;Rigaud B;Netherton T;Cardenas CE;Zhang L;Vedam S;Kry S;Brock KK;Shaw W;O'Reilly F;Parkes J;Burger H;Fakie N;Trauernicht C;Simonds H;Court LE
开发一种用于宫颈癌患者放射治疗计划的临床治疗体积（CTV）和正常组织自动轮廓绘制的工具。开发了一种基于卷积神经网络（CNN）的自动轮廓绘制工具，用于在宫颈癌治疗中描绘3个宫颈CTV和11个正常结构（7个OAR，4个骨性结构），以与放射计划助手（一种基于网络的自动计划生成系统）一起使用。来自单个癌症中心的总计2254个回顾性临床计算机断层扫描（CT）扫描和来自分割挑战的210个CT扫描用于训练和验证基于CNN的自动轮廓工具。通过计算Sørensen-dice相似系数（DSC）以及140次内部CT扫描上自动生成的轮廓与医生绘制的轮廓之间的平均表面距离和Hausdorff距离，评价工具的准确性。一位放射肿瘤学家对来自南非三家医院的30次外部CT扫描自动生成的轮廓进行了评分。我们基于CNN的工具的平均DSC、平均表面距离和Hausdorff距离对于原发性CTV为0.86/0.19 cm/2.02 cm，对于结节CTV为0.81/0.21 cm/2.09 cm，对于PAN CTV为0.76/0.27 cm/2.00 cm，对于膀胱为0.89/0.11 cm/1.07 cm，直肠为0.81/0.18 cm/1.66 cm，脊髓为0.90/0.06 cm/0.65 cm，左股骨为0.94/0.06 cm/0.60 cm，右股骨为0.93/0.07 cm/0.66 cm，左肾为0.94/0.08 cm/0.76 cm，右肾0.95/0.07 cm/0.84 cm，骨盆骨0.93/0.05 cm/1.06 cm，骶骨0.91/0.07 cm/1.25 cm，L4椎体0.91/0.07 cm/0.53 cm，L5椎体0.90/0.08 cm/0.68 cm。根据医生审查，外部测试数据集中平均80%的CTV、97%的风险器官和98%的骨结构轮廓在临床上可接受。我们的基于CNN的自动轮廓绘制工具在内部和外部数据集上表现良好，临床可接受率很高。
To develop a tool for the automatic contouring of clinical treatment volumes (CTVs) and normal tissues for radiotherapy treatment planning in cervical cancer patients. An auto‐contouring tool based on convolutional neural networks (CNN) was developed to delineate three cervical CTVs and 11 normal structures (seven OARs, four bony structures) in cervical cancer treatment for use with the Radiation Planning Assistant, a web‐based automatic plan generation system. A total of 2254 retrospective clinical computed tomography (CT) scans from a single cancer center and 210 CT scans from a segmentation challenge were used to train and validate the CNN‐based auto‐contouring tool. The accuracy of the tool was evaluated by calculating the Sørensen‐dice similarity coefficient (DSC) and mean surface and Hausdorff distances between the automatically generated contours and physician‐drawn contours on 140 internal CT scans. A radiation oncologist scored the automatically generated contours on 30 external CT scans from three South African hospitals. The average DSC, mean surface distance, and Hausdorff distance of our CNN‐based tool were 0.86/0.19 cm/2.02 cm for the primary CTV, 0.81/0.21 cm/2.09 cm for the nodal CTV, 0.76/0.27 cm/2.00 cm for the PAN CTV, 0.89/0.11 cm/1.07 cm for the bladder, 0.81/0.18 cm/1.66 cm for the rectum, 0.90/0.06 cm/0.65 cm for the spinal cord, 0.94/0.06 cm/0.60 cm for the left femur, 0.93/0.07 cm/0.66 cm for the right femur, 0.94/0.08 cm/0.76 cm for the left kidney, 0.95/0.07 cm/0.84 cm for the right kidney, 0.93/0.05 cm/1.06 cm for the pelvic bone, 0.91/0.07 cm/1.25 cm for the sacrum, 0.91/0.07 cm/0.53 cm for the L4 vertebral body, and 0.90/0.08 cm/0.68 cm for the L5 vertebral bodies. On average, 80% of the CTVs, 97% of the organ at risk, and 98% of the bony structure contours in the external test dataset were clinically acceptable based on physician review. Our CNN‐based auto‐contouring tool performed well on both internal and external datasets and had a high rate of clinical acceptability.
登录
查看更多内容
影响因子：
3.8
作者：
通讯作者：
--
DOI：
10.18383/j.tom.2016.00184
发表时间：
2016-12
期刊：
Tomography (Ann Arbor, Mich.)
影响因子：
--
作者：
Cha KH;Hadjiiski LM;Samala RK;Chan HP;Cohan RH;Caoili EM;Paramagul C;Alva A;Weizer AZ
通讯作者：
Weizer AZ
影响因子：
--
作者：
Chuang LT;Temin S;Camacho R;Dueñas-Gonzalez A;Feldman S;Gultekin M;Gupta V;Horton S;Jacob G;Kidd EA;Lishimpi K;Nakisige C;Nam JH;Ngan HYS;Small W;Thomas G;Berek JS
通讯作者：
Berek JS
DOI：
10.1007/s11548-018-1785-8
发表时间：
2018-08-01
影响因子：
3
作者：
Karimi, Davood;Samei, Golnoosh;Salcudean, Septimiu E.
通讯作者：
Salcudean, Septimiu E.
影响因子：
3.5
作者：
Balagopal, Anjali;Kazemifar, Samaneh;Jiang, Steve
通讯作者：
Jiang, Steve