Research Article
Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-Based Noninvasive Digital System
Algorithm 1
Step by step skin cancer segmentation and classification using ViT.
1. Input: IDERMATOSCOPY, SegNetSAM | IDERMATOSCOPY= the 20X Dermatoscopy images | SegNetSAM= the SAM segmentation | 2. Initialization: | i. I = Resize IDERMATOSCOPYinto 224 × 224-pixel | ii. ISEG = Apply SegNetSAM on I | iii. ISEG = Apply Binary Mask on ISEG | 3. ViT: | i. Input: ISEG | ii. IPATCH = Convert ISEG into 14×14 patches | iii. While m: = IPATCH ≤ IPATCH Count | i. ILP[m] = IPATCHUNROLLED[m] × E [][] | ii. D = Concatenate(EPOS[m], ILP[m]) | iv. End While | v. While n <= L do | i. D'n = MSA (LN(Dn-1)) + Dn-1 | ii. Dn = MLP (LN (D'n)) + D'n | vi. End While | vii. IFINAL = LN(DL) | 4. If IFINAL≤ Threshold Value Then | Result: = “Benign” | Else | Result: = “Malignant” | End If | 5. Return Result |
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