Swarm intelligence empowered three-stage ensemble deep learning for arm volume measurement in patients with lymphedema
Swarm intelligence empowered three-stage ensemble deep learning for arm volume measurement in patients with lymphedema
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DOI：
10.1016/j.bspc.2023.105027
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发表时间：
2023-05-16
影响因子：
5.1
通讯作者：
Soltanian-Zadeh, Hamid
中科院分区：
文献类型：
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作者：
Shokouhifar, Ali;Shokouhifar, Mohammad;Soltanian-Zadeh, Hamid
手臂淋巴水肿大多是乳腺癌手术和放射治疗的副作用，可能发生在癌症治疗后。淋巴水肿患者的手臂体积必须在诊断时准确测量，以评估其严重程度，并在治疗期间重新测量，以评估治疗反应。本文提出了一种嵌入相机扫描工具的群体智能三阶段异质/同质集成深度学习模型(简称THENDEL)，它是一种适合于临床日常使用的自动、非侵入性、廉价、可靠、高速的淋巴水肿臂体积测量工具。THENDEL是一个三阶段集成深度学习模型，包括不同的深度特征提取器(第一个异质阶段)、不同的回归器(第二个异质阶段)和一个同质阶段，用于对每个特征提取-回归器进行多次训练。通过基于灰狼优化器的群体智能算法，在离线过程中自动调整THENDEL的超参数(即，异类模型的权重)。THENDEL模型已被成功开发用于测量365名妇女(年龄62.3±9.6岁；体重指数25.4±3.4公斤/平方米；手臂体积2187±373毫升)的730只手臂的体积，包括健康人和淋巴水肿症患者。为了测量手臂的体积，首先从两个垂直方向同时采集两幅图像进行扫描，然后用THENDEL模型估计手臂的体积。实验结果证明了该方法的可靠性，平均绝对误差为36.65mL，平均百分比误差为1.69%，估计的手臂体积与实际手臂体积的相关性为0.992。
Arm lymphedema is mostly a side effect of the breast cancer surgery and radiation therapy, which may happen after the cancer treatment. Arm volume in patients with lymphedema must be accurately measured at the time of diagnosis to assess its severity and remeasured during the treatment to evaluate response to treatment. In this paper, a swarm intelligence three-stage hetero/homogeneous ensemble deep learning model (named THENDEL), embedded in a camera scanning tool, is presented as an automatic, noninvasive, inexpensive, reliable, and high-speed tool for lymphedema arm volume measurement, suitable for daily use in clinics. THENDEL is a three-stage ensemble deep learning model comprising different deep feature extractors (first heterogeneous stage), different regressors (second heterogeneous stage), and a homogeneous stage for multiple training of each feature extractor-regressor. Hyperparameters of THENDEL (i.e., weights of heterogeneous models) are automatically tuned in an offline procedure via a swarm intelligence algorithm based on grey wolf optimizer. The THENDEL model has been successfully developed to measure the volume of 730 arms from 365 women (age, 62.3 +/- 9.6 years; body mass index, 25.4 +/- 3.4 kg/m2; arm volume, 2187 +/- 373 mL), including healthy and patients with lymphedema. To measure the volume of an arm, it is scanned by taking two images at the same time from orthogonal directions, and then, the arm volume is estimated by the THENDEL model. Experimental results demonstrate the reliability of the proposed method by obtaining 36.65 mL mean absolute error, 1.69 % mean percent error, and 0.992 correlation between the estimated and actual arm volumes.