Maxime W. Lafarge

Orcid: 0000-0001-9235-783X

According to our database1, Maxime W. Lafarge authored at least 21 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Mitosis domain generalization in histopathology images - The MIDOG challenge.
Medical Image Anal., 2023

Domain generalization across tumor types, laboratories, and species - insights from the 2022 edition of the Mitosis Domain Generalization Challenge.
CoRR, 2023

CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models.
CoRR, 2023

Multi-task learning for tissue segmentation and tumor detection in colorectal cancer histology slides.
CoRR, 2023

Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Detecting Cells in Histopathology Images with a ResNet Ensemble Model.
Proceedings of the Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology, 2023

2022
Mitosis domain generalization in histopathology images - The MIDOG challenge.
CoRR, 2022

Towards IID representation learning and its application on biomedical data.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Enhancing Local Context of Histology Features in Vision Transformers.
Proceedings of the Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery, 2022

Fine-Grained Hard-Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset.
Proceedings of the Mitosis Domain Generalization and Diabetic Retinopathy Analysis, 2022

2021
Roto-translation equivariant convolutional networks: Application to histopathology image analysis.
Medical Image Anal., 2021

Rotation Invariance and Extensive Data Augmentation: A Strategy for the MItosis DOmain Generalization (MIDOG) Challenge.
Proceedings of the Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis - MICCAI 2021 Challenges: MIDOG 2021, MOOD 2021, and Learn2Reg 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021

2020
Progressively Trained Convolutional Neural Networks for Deformable Image Registration.
IEEE Trans. Medical Imaging, 2020

Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology.
CoRR, 2020

2019
Progressively growing convolutional networks for end-to-end deformable image registration.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019

2018
Deformable image registration using convolutional neural networks.
Proceedings of the Medical Imaging 2018: Image Processing, 2018

Roto-Translation Covariant Convolutional Networks for Medical Image Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Inferring a third spatial dimension from 2D histological images.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Adversarial Training and Dilated Convolutions for Brain MRI Segmentation.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017


  Loading...