The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …

Elucidating the cellular architecture of the human cerebral cortex is central to understanding
our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-…

Deep neural networks are now rivaling human accuracy in several pattern recognition
problems. Compared to traditional classifiers, where features are handcrafted, neural networks …

We present a combined report on the results of three editions of the Cell Tracking Challenge,
an ongoing initiative aimed at promoting the development and objective evaluation of cell …

A model-based method for three-dimensional image segmentation was developed and its
performance assessed in segmentation of volumetric cardiac magnetic resonance (MR) …

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally
conserved across mammals 1 . Here, using high-throughput transcriptomic and epigenomic …

Nonrigid image registration is an important, but time-consuming task in medical image analysis.
In typical neuroimaging studies, multiple image registrations are performed, ie, for atlas-…

In this paper a new cluster validity index is introduced, which assesses the average
compactness and separation of fuzzy partitions generated by the fuzzy c-means algorithm. To …

A fully automated approach to segmentation of the left and right cardiac ventricles from
magnetic resonance (MR) images is reported. A novel multistage hybrid appearance model …

In this paper we propose a method to solve nonrigid image registration through a learning
approach, instead of via iterative optimization of a predefined dissimilarity metric. We design a …