Content-Based Image Retrieval for Multi-Class Volumetric Radiology Images: A Benchmark Study

no code implementations • 15 May 2024 • Farnaz Khun Jush, Steffen Vogler, Tuan Truong, Matthias Lenga

While content-based image retrieval (CBIR) has been extensively studied in natural image retrieval, its application to medical images presents ongoing challenges, primarily due to the 3D nature of medical images.

Croissant: A Metadata Format for ML-Ready Datasets

1 code implementation • 28 Mar 2024 • Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Steffen Vogler, Carole-Jean Wu

Data is a critical resource for Machine Learning (ML), yet working with data remains a key friction point.

Friction Management

Medical Image Retrieval Using Pretrained Embeddings

no code implementations • 22 Nov 2023 • Farnaz Khun Jush, Tuan Truong, Steffen Vogler, Matthias Lenga

A wide range of imaging techniques and data formats available for medical images make accurate retrieval from image databases challenging.

Medical Image Retrieval Retrieval

Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling

1 code implementation • 9 Apr 2021 • Jonas Dippel, Steffen Vogler, Johannes Höhne

This paper presents Contrastive Reconstruction, ConRec - a self-supervised learning algorithm that obtains image representations by jointly optimizing a contrastive and a self-reconstruction loss.

Contrastive Learning Decoder +2