Skin Lesion Classification
36 papers with code • 1 benchmarks • 7 datasets
HAM10000
MSK
BCN_20000
SD-198
Latest papers
Towards Concept-based Interpretability of Skin Lesion Diagnosis using Vision-Language Models
cristianopatricio/concept-based-interpretability-vlm
•
•
Concept-based models naturally lend themselves to the development of inherently interpretable skin lesion diagnosis, as medical experts make decisions based on a set of visual patterns of the lesion.
Self-Supervised Multi-Modality Learning for Multi-Label Skin Lesion Classification
The clinical diagnosis of skin lesion involves the analysis of dermoscopic and clinical modalities.
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment
This paper challenges this assumption and introduces FedPDA, a novel adaptation framework that brings the utility of learning from remote data from Federated Learning into PDA.
SkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification
longman-stan/skindistilvit
•
•
By adding classification heads at each level of the transformer and employing a cascading distillation process, we improve the balanced multi-class accuracy of the base model by 2. 1%, while creating a range of models of various sizes but comparable performance.
ECL: Class-Enhancement Contrastive Learning for Long-tailed Skin Lesion Classification
zylbuaa/ecl
•
•
In this paper, we propose class-Enhancement Contrastive Learning (ECL), which enriches the information of minority classes and treats different classes equally.
FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognition
Representational transfer from publicly available models is a promising technique for improving medical image classification, especially in long-tailed datasets with rare diseases.
Discover and Cure: Concept-aware Mitigation of Spurious Correlation
wuyxin/disc
•
•
Deep neural networks often rely on spurious correlations to make predictions, which hinders generalization beyond training environments.
FCA: Taming Long-tailed Federated Medical Image Classification by Classifier Anchoring
jwicaksana/fca
•
•
To overcome this, we propose federated classifier anchoring (FCA) by adding a personalized classifier at each client to guide and debias the federated model through consistency learning.
Coherent Concept-based Explanations in Medical Image and Its Application to Skin Lesion Diagnosis
cristianopatricio/coherent-cbe-skin
•
•
Early detection of melanoma is crucial for preventing severe complications and increasing the chances of successful treatment.
DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification
However, while a substantial amount of diffusion-based research has focused on generative tasks, few studies have applied diffusion models to general medical image classification.
