5 research outputs found
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Nuclear detection, segmentation and morphometric profiling are essential in
helping us further understand the relationship between histology and patient
outcome. To drive innovation in this area, we setup a community-wide challenge
using the largest available dataset of its kind to assess nuclear segmentation
and cellular composition. Our challenge, named CoNIC, stimulated the
development of reproducible algorithms for cellular recognition with real-time
result inspection on public leaderboards. We conducted an extensive
post-challenge analysis based on the top-performing models using 1,658
whole-slide images of colon tissue. With around 700 million detected nuclei per
model, associated features were used for dysplasia grading and survival
analysis, where we demonstrated that the challenge's improvement over the
previous state-of-the-art led to significant boosts in downstream performance.
Our findings also suggest that eosinophils and neutrophils play an important
role in the tumour microevironment. We release challenge models and WSI-level
results to foster the development of further methods for biomarker discovery
Optimal cell transport in straight channels and networks
\u3cp\u3eFlux of rigid or soft particles (such as drops, vesicles, red blood cells, etc.) in a channel is a complex function of particle concentration, which depends on the details of induced dissipation and suspension structure due to hydrodynamic interactions with walls or between neighboring particles. Through two-dimensional and three-dimensional simulations and a simple model that reveals the contribution of the main characteristics of the flowing suspension, we discuss the existence of an optimal volume fraction for cell transport and its dependence on the cell mechanical properties. The example of blood is explored in detail, by adopting the commonly used modeling of red blood cells dynamics. We highlight the complexity of optimization at the level of a network, due to the antagonist evolution of local volume fraction and optimal volume fraction with the channels diameter. In the case of the blood network, the most recent results on the size evolution of vessels along the circulatory network of healthy organs suggest that the red blood cell volume fraction (hematocrit) of healthy subjects is close to optimality, as far as transport only is concerned. However, the hematocrit value of patients suffering from diverse red blood cel pathologies may strongly deviate from optimality.\u3c/p\u3