Variational Autoencoders for Feature Exploration and Malignancy Prediction of Lung Lesions

arXiv:2311.15719 · cs.CV, cs.AI, cs.LG · Submitted 2023-11-27 · Read on arXiv

cs.CV, cs.AI, cs.LG

Submitted: 2023-11-27

Updated: 2023-11-27

Code: https://github.com/benkeel/VAE_lung_lesion_BMVC

Terminology

• Latent Space — 31× in this paper · explained in 7 episodes
• AUC — 15× in this paper · explained in 2 episodes
• Clustering — 15× in this paper · explained in 2 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• Loss Function — 7× in this paper · explained in 2 episodes
• Sparsity — 3× in this paper · explained in 4 episodes
• Vector Representations — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Artificial Intelligence — 2× in this paper
• Explainability — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Gaussian Error Linear Unit — 2× in this paper
• Generative AI — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Segmentation Masks — 2× in this paper · explained in 2 episodes
• alpha — 2× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Alpha Parameter — 1× in this paper · explained in 2 episodes
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Computed Tomography — 1× in this paper
• Covariate Shift — 1× in this paper · explained in 2 episodes
• D Convolutional Neural Network — 1× in this paper
• Decoupling — 1× in this paper · explained in 2 episodes
• Expectation Maximisation — 1× in this paper
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• International Conference on Computing Methodologies and Communication — 1× in this paper
• Interpretability — 1× in this paper · explained in 15 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Mean Absolute Error — 1× in this paper
• Mean Squared Error — 1× in this paper
• Multi-Layered Perceptron — 1× in this paper
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Structural Similarity Index Measure — 1× in this paper
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Variational Autoencoder (VAE) — 1× in this paper · explained in 3 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Fast and explainable clustering based on sorting
• Learning disentangled representations for explainable chest X-ray classification using Dirichlet VAEs
• Deep Residual Learning for Image Recognition
• Gaussian Error Linear Units (GELUs)
• Dirichlet Variational Autoencoder
• Adam: A Method for Stochastic Optimization
• Auto-Encoding Variational Bayes
• Learning Latent Subspaces in Variational Autoencoders
• Dirichlet Graph Variational Autoencoder
• Interpreting Latent Spaces of Generative Models for Medical Images using Unsupervised Methods
• Autoencoding Variational Inference For Topic Models
• Dirichlet Variational Autoencoder for Text Modeling

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models