Vol.:(0123456789) 1 3 Artificial Life and Robotics https://doi.org/10.1007/s10015-022-00737-y ORIGINAL ARTICLE Automatic measurement of choroidal thickness and vasculature in optical coherence tomography images of eyes with retinitis pigmentosa Tin Tin Khaing 1,2  · Takayuki Okamoto 1  · Chen Ye 3  · Md. Abdul Mannan 3  · Gen Miura 4  · Hirotaka Yokouchi 4  · Kazuya Nakano 5  · Pakinee Aimmanee 2  · Stanislav S. Makhanov 2  · Hideaki Haneishi 3 Received: 10 November 2021 / Accepted: 14 January 2022 © International Society of Artificial Life and Robotics (ISAROB) 2022 Abstract Retinitis pigmentosa (RP) is a group of genetic disorders, characterized by degeneration of photoreceptor cells which is the main cause of choroidal thinning. It is one of the leading causes of blindness worldwide. Thus, an investigation of choroidal changes is required for a better understanding of disease and diagnosis of RP. In this paper, we propose an automatic technique for measuring the choroidal parameters in optical coherence tomography (OCT) images of eyes with RP. The parameters include the total choroidal area (TCA), luminal area (LA), stromal area (SA), and choroidal thickness (CT). We applied our recently proposed, dense dilated U-Net segmentation model, called ChoroidNET, for segmenting the choroid layer and choroidal vessels for our RP dataset. Choroid segmentation is an important task since the measurement results depend on it. Comparison with other state-of-the-art models shows that ChoroidNET provides a better quantitative and qualitative segmentation of the choroid layer and choroidal vessels. Next, we measure the choroidal parameters based on the segmenta- tion results of ChoroidNET. The proposed method achieves high reliability with an intraclass correlation coefcient (0.961, 0.940, 0.826, 0.916) for TCA, LA, SA, and CT, respectively. Keywords Choroid · Segmentation · Measurement · Retinitis pigmentosa · Optical coherence tomography * Takayuki Okamoto t_okamoto@chiba-u.jp Tin Tin Khaing tintin@chiba-u.jp Chen Ye yechen@chiba-u.jp Md. Abdul Mannan mdabdul_mannan@yahoo.com Gen Miura gmiura2@yahoo.co.jp Hirotaka Yokouchi yokouchi123@peace.ocn.ne.jp Kazuya Nakano nakano.kazuya.p2@cc.miyazaki-u.ac.jp Pakinee Aimmanee pakinee@siit.tu.ac.th Stanislav S. Makhanov makhanov@siit.tu.ac.th Hideaki Haneishi haneishi@faculty.chiba-u.jp 1 Graduate School of Science and Engineering, Chiba University, Chiba 263-8522, Japan 2 Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12000, Thailand 3 Center for Frontier Medical Engineering, Chiba University, Chiba 263-8522, Japan 4 Department of Ophthalmology and Visual Science, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan 5 Institute for Tenure Track Promotion, University of Miyazaki, Miyazaki 889-2192, Japan