Ludovic Roux

Ludovic Roux, Alexandre Gouaillard

With COVID-19, the interest for digital interactions has raised, putting in turn real-time (or low-latency) codecs into a new light. Most of the codec research has been traditionally focusing on coding efficiency, while very little literature exist on real-time codecs. It is shown how the speed at which content is made available impacts both latency and throughput. The authors introduce a new test set up, integrating a paced reader, which allows to run codec in the same condition as real-time media capture. Quality measurements using VMAF, as well as multiple speed measurements are made on encoding of HD and full HD video sequences, both at 25 fps and 50 fps to compare the respective performances of several implementations of the H.264, H.265, VP8, VP9 and AV1 codecs.

H. Irshad, A. Gouaillard, L. Roux et al.

Accurate detection of mitosis plays a critical role in breast cancer histopathology. Manual detection and counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Multispectral imaging is a recent medical imaging technology, proven successful in increasing the segmentation accuracy in other fields. This study aims at improving the accuracy of mitosis detection by developing a specific solution using multispectral and multifocal imaging of breast cancer histopathological data. We propose to enable clinical routine-compliant quality of mitosis discrimination from other objects. The proposed framework includes comprehensive analysis of spectral bands and z-stack focus planes, detection of expected mitotic regions (candidates) in selected focus planes and spectral bands, computation of multispectral spatial features for each candidate, selection of multispectral spatial features and a study of different state-of-the-art classification methods for candidates classification as mitotic or non mitotic figures. This framework has been evaluated on MITOS multispectral medical dataset and achieved 60% detection rate and 57% F-Measure. Our results indicate that multispectral spatial features have more information for mitosis classification in comparison with white spectral band features, being therefore a very promising exploration area to improve the quality of the diagnosis assistance in histopathology.