A novel model for diabetic macular edema segmentation based on improved SOLO_v2(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2023年第1期
- Page:
- 24-30
- Research Field:
- 医学影像物理
- Publishing date:
Info
- Title:
- A novel model for diabetic macular edema segmentation based on improved SOLO_v2
- Author(s):
- ZHENG Zongsheng; TANG Pengfei; WANG Zhenhua; LU Peng
- College of Information Technology, Shanghai Ocean University, Shanghai 201306, China
- Keywords:
- Keywords: diabetic macular edema instance segmentation feature enhancement non-maximum suppression
- PACS:
- R318；TP391.41
- DOI:
- DOI:10.3969/j.issn.1005-202X.2023.01.005
- Abstract:
- Abstract: Diabetic macular edema (DME) is a common cause of visual impairment in diabetic patients. Optical coherence tomography (OCT) can enhance the early detection and prevention of diabetic retinopathy. At present, there are a lot of speckle noises and small target areas in the DME region in OCT images, and the existing instance segmentation methods have some problems such as missing segmentation. To address the above issues, SOLO_v2 model is improved by feature pyramid transformer, and a novel model (SOLO-OCT model) is proposed for DME segmentation. The proposed method improves the quality of the input image by removing the speckle noises from the image using dual-domain filtering algorithm, and enhances the models ability to recognize and learn small target areas by feature pyramid transformer, and alleviates the problem of missing segmentation for small target areas through improved non-maximum suppression. The SOLO-OCT model is compared with other instance segmentation models (Mask R-CNN, SOLO and SOLO_v2) to evaluate its performance in DME segmentation. Compared with Mask R-CNN, SOLO and SOLO_v2 models, SOLO-OCT model improves the segmentation accuracy of DME region (mAP) by about 3.1% and raises the segmentation accuracy of small-target DME region (APs) by about 2.2%, but the processing time of a single image (Fps) is increased by only about 0.009 9 s. The proposed SOLO-OCT model for DME segmentation can be used for large-scale screening for diabetic retinopathy.
Last Update: 2023-01-07