Research Article
DeepLab and Bias Field Correction Based Automatic Cone Photoreceptor Cell Identification with Adaptive Optics Scanning Laser Ophthalmoscope Images
Table 1
Performance measures obtained from cone photoreceptor cell identification algorithms.
| | Methods | Precision | Recall | score |
| | Graph theory based algorithm [15] | 98.2% | 98.5% | 98.3% | | Proposed algorithm | 96.7% | 94.6% | 95.7% | | Watershed based algorithm [18] | 93.2% | 96.6% | 94.9% | | -means clustering based algorithm [26] | 93.4% | 95.2% | 94.3% | | Superpixels based algorithm [25] | 80.1% | 93.5% | 86.3% |
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