The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
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- Type
- article
- Published
- 2018-08-14
- Cited by
- 3,184
- References
- 29
- Access
- Open access
- OpenAlex
- https://openalex.org/W2794825826
Keywords
Dermatoscopy, Workflow, Ground truth, Training set, Benchmark (surveying)
References
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- Improvement of early recognition of lentigo maligna using dermatoscopy.
- Dermatoscopy of facial actinic keratosis, intraepidermal carcinoma, and invasive squamous cell carcinoma: a progression model.
- Dermatoscopy of flat pigmented facial lesions
- Dermatoscopy of pigmented Bowen's disease.
- PH2 - A dermoscopic image database for research and benchmarking
- The dermatoscopic universe of basal cell carcinoma
- ImageNet: A large-scale hierarchical image database
- Meta‐analysis of digital dermoscopy follow‐up of melanocytic skin lesions: a study on behalf of the International Dermoscopy Society
- Dermatoscopy of flat pigmented facial lesions: diagnostic challenge between pigmented actinic keratosis and lentigo maligna
- Diagnostic accuracy of dermatoscopy for melanocytic and nonmelanocytic pigmented lesions.
- Rethinking the Inception Architecture for Computer Vision
- Dermatologist–level classification of skin cancer with deep neural networks
- The value of reflectance confocal microscopy in diagnosis of flat pigmented facial lesions: a prospective study
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- Lesion Attributes Segmentation for Melanoma Detection with Deep Learning
- Skin Lesion Classification Via Combining Deep Learning Features and Clinical Criteria Representations
- Dermatoscopy of Neoplastic Skin Lesions: Recent Advances, Updates, and Revisions
- Diagnostic accuracy of content‐based dermatoscopic image retrieval with deep classification features
- Domain-specific classification-pretrained fully convolutional network encoders for skin lesion segmentation
- Convolutional Neural Network Algorithm with Parameterized Activation Function for Melanoma Classification
- Deep Learning and Handcrafted Method Fusion: Higher Diagnostic Accuracy for Melanoma Dermoscopy Images
- A Hierarchical Approach to Skin Lesion Classification
- Topological approaches to skin disease image analysis
- Deep Ensemble Learning for Skin Lesion Classification from Dermoscopic Images
- Sind Computeralgorithmen besser als Dermatologen?
- A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task.
- Melanomdiagnose mithilfe künstlicher Intelligenz
- Learning Interpretable Disentangled Representations using Adversarial VAEs
- Towards Automated Melanoma Detection With Deep Learning: Data Purification and Augmentation
- Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images
- Feasibility of Automated Deep Learning Design for Medical Image Classification by Healthcare Professionals with Limited Coding Experience
- Integrity Verification in Medical Image Retrieval Systems using Spread Spectrum Steganography
- Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study
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