CellProfiler has enabled the scientific research community to create flexible, modular image
analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new …

Identifying nuclei is often a critical first step in analyzing microscopy images of cells and
classical image processing algorithms are most commonly used for this task. Recent …

This paper describes the participation of the ECOUAN team in the LifeCLEF 2015 challenge.
We used a deep learning approach in which the complete system was learned without hand…

The Flickr30k dataset has become a standard benchmark for sentence-based image
description. This paper presents Flickr30k Entities, which augments the 158k captions from …

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic
differences among a variety of cell populations. It paves the way to studying biological …

Segmenting the nuclei of cells in microscopy images is often the first step in the quantitative
analysis of imaging data for biological and biomedical applications. Many bioimage analysis …

We present an active detection model for localizing objects in scenes. The model is class-specific
and allows an agent to focus attention on candidate regions for identifying the correct …

Resection and radiofrequency ablation (RFA) are treatment options for hepatocellular
carcinoma (HCC) <3 cm; there is interest in expanding the role of ablation to 3‐5 cm. RFA is …

Background & Aims Portal vein embolization (PVE) is a standard technique for patients not
amenable to liver resection due to small future liver remnant ratio (FLR). Radiation lobectomy …

Single-cell segmentation is typically a crucial task of image-based cellular analysis. We
present nucleAIzer, a deep-learning approach aiming toward a truly general method for …