AI in Dermatology

Skin Lesion Classification

ABCDE Criteria

import torchvision.models as models

class SkinLesionClassifier(nn.Module):
    def __init__(self, n_classes=7):
        super().__init__()
        self.backbone = models.inception_v3(pretrained=True)
        self.backbone.fc = nn.Sequential(
            nn.Linear(2048, 512), nn.ReLU(), nn.Dropout(0.5),
            nn.Linear(512, n_classes))

    def forward(self, x):
        return self.backbone(x)

CLASSES = ['Melanoma', 'Nevus', 'Basal Cell', 'Actinic Keratosis',
           'Benign Keratosis', 'Dermatofibroma', 'Vascular Lesion']

Melanoma Detection

Grad-CAM Explainability

class GradCAM:
    def generate_heatmap(self, input_image, class_idx):
        output = self.model(input_image)
        output[0, class_idx].backward()
        gradients = self.model.get_gradient()
        weights = torch.mean(gradients, dim=[2, 3], keepdim=True)
        cam = torch.relu(torch.sum(weights * self.model.get_activation(), dim=1))
        return cam / cam.max()

Lesion Segmentation

Evaluation