Publications de Raphael Sznitman

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We propose an active learning approach to image segmentation that exploits geometric priors to speed up and streamline the annotation process. It can be applied for both background foreground and multi-class segmentation tasks in 2D images and 3D image vol ...

Background: Maximum Intensity Projections (MIP) of neuronal dendritic trees obtained from confocal microscopy are frequently used to study the relationship between tree morphology and mechanosensory function in the model organism C. elegans. Extracting den ...

We propose an Active Learning approach to training a segmentation classifier that exploits geometric priors to streamline the annotation process in 3D image volumes. To this end, we use these priors not only to select voxels most in need of annotation but ...

Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not ...

Scanning Electron Microscopy (SEM) is an invaluable tool for biologists and neuroscientists to study brain structure at the intra- cellular level. While able to image tissue samples with up to 5nm isotropic resolution, image acquisition is prohibitively sl ...

We present a new approach for matching sets of branching curvilinear structures that form graphs embedded in R2 or R3 and may be subject to deformations. Unlike earlier methods, ours does not rely on local appearance similarity nor does require a good init ...

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. Instead of reconstructing structures in each image independently, we do so for all images simultaneous ...

Cascade-style approaches to implementing ensemble classifiers can deliver significant speed-ups at test time. While highly effective, they remain challenging to tune and their overall performance depends on the availability of large validation sets to esti ...

We presented an approach for speeding-up image acquisition when tasked with localizing specific structures in FIB-SEM imagery. It exploits the fact that low-quality images can be acquired faster than higher-quality ones and yet be sufficient for inference ...

With widening interests in using model organisms for reverse genetic approaches and biomimmetic micro-robotics, motility phenotyping of the nematode Caenorhabditis elegans is expanding across a growing array of locomotive environments. One ongoing bottlene ...

For biologists studying the morphology of cells, Electron Microscopy (EM) is the method of choice with its {\it nm} resolution, across increasingly larger volumes. However, the time necessary to acquire such image series is long and often limits the amount ...

The use of 3D Magnetic Resonance Imaging (MRI) has attracted growing attention for the purpose of diagnosis and treatment planning of intraocular ocular cancers. Precise segmentation of such tumors are highly important to characterize tumors, their progres ...

We present a general approach for solving the point-cloud matching problem for the case of mildly nonlinear transformations. Our method quickly finds a coarse approximation of the solution by exploring a reduced set of partial matches using an approach to ...

Automatic visual detection of instruments in minimally invasive surgery (MIS) can significantly augment the procedure experience for operating clinicians. In this paper, we present a novel technique for detecting surgical instruments by constructing a robu ...

In the context of retinal microsurgery, visual tracking of instruments is a key component of robotics assistance. The difficulty of the task and major reason why most existing strategies fail on {\it in-vivo} image sequences lies in the fact that complex a ...

Purpose: We present a 3-dimensional patient-specific eye model from magnetic resonance imaging (MRI) for proton therapy treatment planning of uveal melanoma (UM). During MRI acquisition of UM patients, the point fixation can be difficult and, together with ...

We propose a novel approach to reconstructing curvilinear tree structures evolving over time, such as road networks in 2D aerial images or neural structures in 3D microscopy stacks acquired in vivo. To enforce temporal consistency, we simultaneously proces ...

This paper considers the task of finding a target location by making a limited number of sequential observations. Each observation results from evaluating an imperfect classifier of a chosen cost and accuracy on an interval of chosen length and position. W ...

Raphael Sznitman

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Geometry in active learning for binary and multi-class image segmentation

Dendritic tree extraction from noisy maximum intensity projection images in C-elegans

Introducing Geometry in Active Learning for Image Segmentation

Unified Detection and Tracking of Instruments during Retinal Microsurgery

Flash Scanning Electron Microscopy

Non-Rigid Graph Registration using Active Testing Search

Reconstructing Evolving Tree Structures in Time Lapse Sequences

Fast Object Detection with Entropy-Driven Evaluation

Efficient scanning for em based target localization

Caenorhabditis elegant segmentation using texture-based models for motility phenotyping

Efficient Scanning for EM Based Target Localization

Ocular Structures Segmentation from Multi-sequences MRI Using 3D Unet with Fully Connected CRFs

Active Testing Search for Point Cloud Matching

Fast Part-Based Classification for Instrument Detection in Minimally Invasive Surgery

Data-Driven Visual Tracking in Retinal Microsurgery

Personalized Anatomic Eye Model From T1-Weighted Volume Interpolated Gradient Echo Magnetic Resonance Imaging of Patients With Uveal Melanoma

Reconstructing Evolving Tree Structures in Time Lapse Sequences by Enforcing Time-Consistency

An Optimal Policy for Target Localization with Application to Electron Microscopy

Active Learning for Delineation of Curvilinear Structures