Edema Estimation From Facial Images Taken Before and After Dialysis via Contrastive Multi-Patient Pre-Training

被引：1

作者：

Akamatsu, Yusuke ^{[1
]}

Onishi, Yoshifumi ^{[1
]}

Imaoka, Hitoshi ^{[1
]}

Kameyama, Junko ^{[2
,3
]}

Tsurushima, Hideo ^{[2
]}

机构：

[1] NEC Corp Ltd, Biometr Res Labs, Kawasaki 2118666, Japan

[2] Univ Tsukuba, Fac Med, Dept Neurosurg, Tsukuba, Japan

[3] Univ Tokyo, Inst Med Sci, Minato ku, Tokyo, Japan

来源：

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS | 2023年 / 27卷 / 03期

关键词：

Estimation; Fluids; Biomedical measurement; Diseases; Data models; Biomedical imaging; Task analysis; Edema; kidney disease; renal failure; dialysis; facial image; convolutional neural network; contrastive learning; pre-training; transfer learning; HEMODIALYSIS; MORTALITY; LEG;

D O I：

10.1109/JBHI.2022.3227517

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Edema is a common symptom of kidney disease, and quantitative measurement of edema is desired. This paper presents a method to estimate the degree of edema from facial images taken before and after dialysis of renal failure patients. As tasks to estimate the degree of edema, we perform pre- and post-dialysis classification and body weight prediction. We develop a multi-patient pre-training framework for acquiring knowledge of edema and transfer the pre-trained model to a model for each patient. For effective pre-training, we propose a novel contrastive representation learning, called weight-aware supervised momentum contrast (WeightSupMoCo). WeightSupMoCo aims to make feature representations of facial images closer in similarity of patient weight when the pre- and post-dialysis labels are the same. Experimental results show that our pre-training approach improves the accuracy of pre- and post-dialysis classification by 15.1% and reduces the mean absolute error of weight prediction by 0.243 kg compared with training from scratch. The proposed method accurately estimate the degree of edema from facial images; our edema estimation system could thus be beneficial to dialysis patients.

引用

页码：1419 / 1430

页数：12