Search Results for author: Raphael Sznitman

Found 27 papers, 10 papers with code

DeepPyramid: Enabling Pyramid View and Deformable Pyramid Reception for Semantic Segmentation in Cataract Surgery Videos

1 code implementation4 Jul 2022 Negin Ghamsarian, Mario Taschwer, Raphael Sznitman, Klaus Schoeffmann

Semantic segmentation in cataract surgery has a wide range of applications contributing to surgical outcome enhancement and clinical risk reduction.

Semantic Segmentation

Consistency-preserving Visual Question Answering in Medical Imaging

1 code implementation27 Jun 2022 Sergio Tascon-Morales, Pablo Márquez-Neila, Raphael Sznitman

Visual Question Answering (VQA) models take an image and a natural-language question as input and infer the answer to the question.

Question Answering Visual Question Answering +1

Data Invariants to Understand Unsupervised Out-of-Distribution Detection

no code implementations26 Nov 2021 Lars Doorenbos, Raphael Sznitman, Pablo Márquez-Neila

Motivated by a simple thought experiment, we propose a characterization of U-OOD based on the invariants of the training dataset.

OOD Detection Out-of-Distribution Detection

A Positive/Unlabeled Approach for the Segmentation of Medical Sequences using Point-Wise Supervision

1 code implementation18 Jul 2021 Laurent Lejeune, Raphael Sznitman

While most methods of this kind assume that the proportion of positive samples in the data is known a-priori, we introduce a novel self-supervised method to estimate this prior efficiently by combining a Bayesian estimation framework and new stopping criteria.

CataNet: Predicting remaining cataract surgery duration

1 code implementation21 Jun 2021 Andrés Marafioti, Michel Hayoz, Mathias Gallardo, Pablo Márquez Neila, Sebastian Wolf, Martin Zinkernagel, Raphael Sznitman

Cataract surgery is a sight saving surgery that is performed over 10 million times each year around the world.

Volumetric Quantitative Ablation Margins for Assessment of Ablation Completeness in Thermal Ablation of Liver Tumors

1 code implementation Frontiers in Oncology, Cancer Imaging and Image-directed interventions 2021 Raluca-Maria Sandu, Iwan Polucci, Simeon J. S. Ruiter, Raphael Sznitman, Koert P. de Jong, Jacob Freedman, Stefan Weber and Pascale Tinguely

For subcapsular tumors, the underestimation of tumor coverage by the ablation volume when applying an unadjusted QAM method was confirmed, supporting the benefits of using the proposed algorithm for QAM computation in these cases.

Decision Making

Fused Detection of Retinal Biomarkers in OCT Volumes

no code implementations16 Jul 2019 Thomas Kurmann, Pablo Márquez-Neila, Siqing Yu, Marion Munk, Sebastian Wolf, Raphael Sznitman

In this context, we present a method that automatically predicts the presence of biomarkers in OCT cross-sections by incorporating information from the entire volume.

Concept-Centric Visual Turing Tests for Method Validation

no code implementations15 Jul 2019 Tatiana Fountoukidou, Raphael Sznitman

To do this, we make use of a Twenty Questions paradigm whereby we use a probabilistic model to characterize the method's capacity to grasp task-specific concepts, and we introduce a strategy to sequentially query the method according to its previous answers.

BIG-bench Machine Learning

Deep Multi Label Classification in Affine Subspaces

no code implementations10 Jul 2019 Thomas Kurmann, Pablo Marquez Neila, Sebastian Wolf, Raphael Sznitman

We evaluate the method using two MLC medical imaging datasets and show a large performance increase compared to previous multi-label frameworks.

Classification General Classification +3

Iterative multi-path tracking for video and volume segmentation with sparse point supervision

no code implementations27 Aug 2018 Laurent Lejeune, Jan Grossrieder, Raphael Sznitman

Our object model is then used in a graph-based optimization problem that takes into account all provided locations and the image data in order to infer the complete pixel-wise segmentation.

BIG-bench Machine Learning

Supervised Machine Learning for Analysing Spectra of Exoplanetary Atmospheres

1 code implementation11 Jun 2018 Pablo Marquez-Neila, Chloe Fisher, Raphael Sznitman, Kevin Heng

Machine learning has previously been used to determine which molecules to include in the model, but the retrieval itself was still performed using standard methods.

Earth and Planetary Astrophysics Atmospheric and Oceanic Physics Data Analysis, Statistics and Probability

Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery

1 code implementation18 Oct 2017 Thomas Kurmann, Pablo Marquez Neila, Xiaofei Du, Pascal Fua, Danail Stoyanov, Sebastian Wolf, Raphael Sznitman

An additional advantage of our approach is that instrument detection at test time is achieved while avoiding the need for scale-dependent sliding window evaluation.

Pose Estimation

Pathological OCT Retinal Layer Segmentation using Branch Residual U-shape Networks

no code implementations16 Jul 2017 Stefanos Apostolopoulos, Sandro De Zanet, Carlos Ciller, Sebastian Wolf, Raphael Sznitman

The automatic segmentation of retinal layer structures enables clinically-relevant quantification and monitoring of eye disorders over time in OCT imaging.

Expected exponential loss for gaze-based video and volume ground truth annotation

no code implementations16 Jul 2017 Laurent Lejeune, Mario Christoudias, Raphael Sznitman

Many recent machine learning approaches used in medical imaging are highly reliant on large amounts of image and ground truth data.

Semantic Segmentation

RetiNet: Automatic AMD identification in OCT volumetric data

no code implementations12 Oct 2016 Stefanos Apostolopoulos, Carlos Ciller, Sandro I. De Zanet, Sebastian Wolf, Raphael Sznitman

In much the same way, acquiring ground truth information for each cross-section is expensive and time consuming.

Geometry in Active Learning for Binary and Multi-class Image Segmentation

no code implementations29 Jun 2016 Ksenia Konyushkova, Raphael Sznitman, Pascal Fua

Our approach combines geometric smoothness priors in the image space with more traditional uncertainty measures to estimate which pixels or voxels are the most informative, and thus should to be annotated next.

Active Learning Semantic Segmentation

Active Learning for Delineation of Curvilinear Structures

no code implementations CVPR 2016 Agata Mosinska, Raphael Sznitman, Przemysław Głowacki, Pascal Fua

Many recent delineation techniques owe much of their increased effectiveness to path classification algorithms that make it possible to distinguish promising paths from others.

Active Learning General Classification

Introducing Geometry in Active Learning for Image Segmentation

no code implementations ICCV 2015 Ksenia Konyushkova, Raphael Sznitman, Pascal Fua

We propose an Active Learning approach to training a segmentation classifier that exploits geometric priors to streamline the annotation process in 3D image volumes.

Active Learning Semantic Segmentation

Reconstructing Evolving Tree Structures in Time Lapse Sequences

no code implementations CVPR 2014 Przemyslaw Glowacki, Miguel Amavel Pinheiro, Engin Turetken, Raphael Sznitman, Daniel Lebrecht, Jan Kybic, Anthony Holtmaat, Pascal Fua

We propose an approach to reconstructing tree structures that evolve over time in 2D images and 3D image stacks such as neuronal axons or plant branches.

Active Testing for Face Detection and Localization

no code implementations27 Mar 2010 Raphael Sznitman, Bruno Jedynak

We provide a novel search technique, which uses a hierarchical model and a mutual information gain heuristic to efficiently prune the search space when localizing faces in images.

Face Detection

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