Analysis of the ISIC image datasets: Usage, benchmarks and recommendations

Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context

(2021) Veronica Rotemberg et al.   Scientific Data

DSNet: Automatic dermoscopic skin lesion segmentation

(2020) Md. Kamrul Hasan et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Melanoma and Nevus Skin Lesion Classification Using Handcraft and Deep Learning Feature Fusion via Mutual Information Measures

(2020) Jose-Agustin Almaraz-Damian et al.   Entropy

A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification

(2020) Yutong Xie et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

The Development of a Skin Cancer Classification System for Pigmented Skin Lesions Using Deep Learning

(2020) Shunichi Jinnai et al.   Biomolecules

Effects of Label Noise on Deep Learning-Based Skin Cancer Classification

(2020) Achim Hekler et al.   Frontiers in Medicine

SESV: Accurate Medical Image Segmentation by Predicting and Correcting Errors

(2020) Yutong Xie et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task

(2019) Titus J. Brinker et al.   EUROPEAN JOURNAL OF CANCER

Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task

(2019) Titus J. Brinker et al.   EUROPEAN JOURNAL OF CANCER

Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study

(2019) Philipp Tschandl et al.   LANCET ONCOLOGY

Classification of skin lesions using transfer learning and augmentation with Alex-net

(2019) Khalid M. Hosny et al.   PLoS One

Efficient skin lesion segmentation using separable-Unet with stochastic weight averaging

(2019) Peng Tang et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Deep neural networks are superior to dermatologists in melanoma image classification

(2019) Titus J. Brinker et al.   EUROPEAN JOURNAL OF CANCER

Superior skin cancer classification by the combination of human and artificial intelligence

(2019) Achim Hekler et al.   EUROPEAN JOURNAL OF CANCER

Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

(2018) H A Haenssle et al.   ANNALS OF ONCOLOGY

Deep learning-based, computer-aided classifier developed with a small dataset of clinical images surpasses board-certified dermatologists in skin tumor diagnosis

(2018) Y. Fujisawa et al.   BRITISH JOURNAL OF DERMATOLOGY

Deep Constrained Siamese Hash Coding Network and Load-Balanced Locality-Sensitive Hashing for Near Duplicate Image Detection

(2018) Weiming Hu et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Skin Cancer Classification using Convolutional Neural Networks: Systematic Review (Preprint)

(2018) Titus Josef Brinker et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

(2018) Philipp Tschandl et al.   Scientific Data

Fusing fine-tuned deep features for skin lesion classification

(2018) Amirreza Mahbod et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Optimised deep learning features for improved melanoma detection

(2018) Tomáš Majtner et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE