OSA CONFERENCE ABSTRACT Darkfield microscopy demonstrated that MUC16 shed from ovarian cancer tumors is present on the surface of white cells, and when quantified in a patient for two years was predictive of the disease course.
Sierra Research’s team has developed the algorithms that lead to the data of the following article: https://pubs.acs.org/doi/abs/10.1021/acssensors.0c00567 Plasmonic nanoparticles conjugated with anti-CA125 antibody were used to quantify MUC16 binding on leukocytes of ovarian cancer patients. Results show an elevated presence of MUC16 on ovarian cnacer patients with respect to healthy controls. Further, the assay was…
Given a biomarker regression network, what is the effect of training with different cost functions? In this conference publications, Sierra’s researcher investigate the influence of training with L1, L2, L1 in logarithmic scale or L2 in logarithmic scale for the problem of Agatston score regression from CT volumetric images center at the heart. There is…
Can we generate a single multi-structure segmentation network from partially annotated datasets? In this conference paper Sierra’s researchers in conjunction with Brigham and Women’s Hospital answer such question, showing that a) it is equivalent to use a single unet and b) that adding convolutions on the skip connections further improve segmentation results. The full article…
Can artificial intelligence regression networks locate the regions of interest from whom they are obtaining their value? In this conference article, Sierra’s researchers explore such question. From Computer Tomography axial slices obtained at the level of the transversal aorta, and the areas of their pectoralis muscle and subcutaneous fat, we have been able to perform…
H-EM: an algorithm for simultaneous cell diameter and intensity quantification in low-resolution imaging cytometry Sierra’s Researcher in collaboration with URJC and Madrid-MIT M+Vision Consortium have published a PlosOne paper on low-resolution cell analysis. You can find the whole article at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0222265