MYC Rearrangement Prediction From LYSA Whole Slide Images in Large B-Cell Lymphoma: A Multicentric Validation of Self-supervised Deep Learning Models.

Large B-cell lymphoma (LBCL) is a heterogeneous lymphoid malignancy in which MYC gene rearrangement (MYC-R) is associated with a poor prognosis, prompting the recommendation for more intensive treatment. MYC-R detection relies on fluorescence in situ hybridization method which is time consuming, expensive, and not available in all laboratories. Automating MYC-R detection on hematoxylin-and-eosin-stained whole slide images of LBCL would decrease the need for costly molecular testing and improve pathologists' productivity.

Improved 3D U-Net robustness against JPEG 2000 compression for male pelvic organ segmentation in radiotherapy.

Automation of organ segmentation, via convolutional neural networks (CNNs), is key to facilitate the work of medical practitioners by ensuring that the adequate radiation dose is delivered to the target area while avoiding harmful exposure of healthy organs. The issue with CNNs is that they require large amounts of data transfer and storage which makes the use of image compression a necessity. Compression will affect image quality which in turn affects the segmentation process.

Generation of squeezed light vacuum enabled by coherent population trapping.

We demonstrate the possibility to generate squeezed vacuum states of light by four wave mixing (FWM) enabled coherent population trapping in a metastable helium cell at room temperature. Contrary to usual FWM far detuned schemes, we work at resonance with an atomic transition. We investigate the properties of such states and show that the noise variances of the squeezed and anti-squeezed quadratures cannot be explained by the simple presence of losses.

Domain adversarial networks and intensity-based data augmentation for male pelvic organ segmentation in cone beam CT.

In radiation therapy, a CT image is used to manually delineate the organs and plan the treatment. During the treatment, a cone beam CT (CBCT) is often acquired to monitor the anatomical modifications. For this purpose, automatic organ segmentation on CBCT is a crucial step.

Coherent Population Oscillation-Based Light Storage.

We theoretically study the propagation and storage of a classical field in a Λ-type atomic medium using coherent population oscillations (CPOs). We show that the propagation eigenmodes strongly relate to the different CPO modes of the system. Light storage in such modes is discussed by introducing a "populariton" quantity, a mixture of populations and field, by analogy to the dark state polariton used in the context of electromagnetically induced transparency light storage protocol.