# Skin Lesion Recognition with Class-Hierarchy Regularized Hyperbolic Embeddings

arXiv: https://arxiv.org/abs/2209.05842 · HTML: https://mlsanity.com/paper/2209.05842/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 16 references that are in the map.
- First posted on arXiv 13 Sep 2022.

## Builds on (most cited first, 10 of 10)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Poincar'e Embeddings for Learning Hierarchical Representations](https://mlsanity.com/paper/1705.08039/) (2017)
- [Hyperbolic Image Embeddings](https://mlsanity.com/paper/1904.02239/) (2019)
- [Representation Tradeoffs for Hyperbolic Embeddings](https://mlsanity.com/paper/1804.03329/) (2018)
- [Hyperbolic Entailment Cones for Learning Hierarchical Embeddings](https://mlsanity.com/paper/1804.01882/) (2018)
- [Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks](https://mlsanity.com/paper/1912.09393/) (2019)
- [B-CNN: Branch Convolutional Neural Network for Hierarchical Classification](https://mlsanity.com/paper/1709.09890/) (2017)
- [Leveraging Class Hierarchies with Metric-Guided Prototype Learning](https://mlsanity.com/paper/2007.03047/) (2020)
- [Hierarchical Classification of Pulmonary Lesions: A Large-Scale Radio-Pathomics Study](https://mlsanity.com/paper/2010.04049/) (2020)
- [Hierarchical Class-Based Curriculum Loss](https://mlsanity.com/paper/2006.03629/) (2020)

## Built on by (most cited first, 19 of 19)

- [Hyperbolic Deep Learning in Computer Vision: A Survey](https://mlsanity.com/paper/2305.06611/) (2023)
- [Fully Hyperbolic Convolutional Neural Networks for Computer Vision](https://mlsanity.com/paper/2303.15919/) (2023)
- [Poincar'e ResNet](https://mlsanity.com/paper/2303.14027/) (2023)
- [Hyperbolic Audio-visual Zero-shot Learning](https://mlsanity.com/paper/2308.12558/) (2023)
- [HLFormer: Enhancing Partially Relevant Video Retrieval with Hyperbolic Learning](https://mlsanity.com/paper/2507.17402/) (2025)
- [Inducing Neural Collapse to a Fixed Hierarchy-Aware Frame for Reducing Mistake Severity](https://mlsanity.com/paper/2303.05689/) (2023)
- [Learning Visual Hierarchies in Hyperbolic Space for Image Retrieval](https://mlsanity.com/paper/2411.17490/) (2024)
- [Investigating the Quality of DermaMNIST and Fitzpatrick17k Dermatological Image Datasets](https://mlsanity.com/paper/2401.14497/) (2024)
- [Low-distortion and GPU-compatible Tree Embeddings in Hyperbolic Space](https://mlsanity.com/paper/2502.17130/) (2025)
- [Hyperbolic Geometry in Computer Vision: A Survey](https://mlsanity.com/paper/2304.10764/) (2023)
- [Curvature Learning for Generalization of Hyperbolic Neural Networks](https://mlsanity.com/paper/2508.17232/) (2025)
- [Balanced Hyperbolic Embeddings Are Natural Out-of-Distribution Detectors](https://mlsanity.com/paper/2506.10146/) (2025)
- [Hyperbolic Kernel Graph Neural Networks for Neurocognitive Decline Analysis from Multimodal Brain Imaging](https://mlsanity.com/paper/2507.02908/) (2025)
- [Minimizing Hyperbolic Embedding Distortion with LLM-Guided Hierarchy Restructuring](https://mlsanity.com/paper/2511.20679/) (2025)
- [HypCBC: Domain-Invariant Hyperbolic Cross-Branch Consistency for Generalizable Medical Image Analysis](https://mlsanity.com/paper/2602.03264/) (2026)
- [PiercingEye: Dual-Space Video Violence Detection with Hyperbolic Vision-Language Guidance](https://mlsanity.com/paper/2504.18866/) (2025)
- [HyperHELM: Hyperbolic Hierarchy Encoding for mRNA Language Modeling](https://mlsanity.com/paper/2509.24655/) (2025)
- [hYOLO Model: Enhancing Object Classification with Hierarchical Context in YOLOv8](https://mlsanity.com/paper/2510.23278/) (2025)
- [Online Continual Learning with Dynamic Label Hierarchies](https://mlsanity.com/paper/2605.11742/) (2026)

## Abstract (arXiv)

In practice, many medical datasets have an underlying taxonomy defined over the disease label space. However, existing classification algorithms for medical diagnoses often assume semantically independent labels. In this study, we aim to leverage class hierarchy with deep learning algorithms for more accurate and reliable skin lesion recognition. We propose a hyperbolic network to learn image embeddings and class prototypes jointly. The hyperbola provably provides a space for modeling hierarchical relations better than Euclidean geometry. Meanwhile, we restrict the distribution of hyperbolic prototypes with a distance matrix that is encoded from the class hierarchy. Accordingly, the learned prototypes preserve the semantic class relations in the embedding space and we can predict the label of an image by assigning its feature to the nearest hyperbolic class prototype. We use an in-house skin lesion dataset which consists of around 230k dermoscopic images on 65 skin diseases to verify our method. Extensive experiments provide evidence that our model can achieve higher accuracy with less severe classification errors than models without considering class relations.