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Myelodysplastic syndromes (MDS) are relatively rare blood diseases that vary widely in their severity, symptoms, and tendency to progress to acute myeloid leukemia and therefore require precise diagnosis and classification1,2 . Flow cytometry immunophenotyping of bone marrow cells could be helpful in making the diagnosis of MDS3. Due to natural properties of the fluorescent dyes used in flow cytometry, raw digital data from the instrument must be compensated to account for the spillover of signal between fluorochromes.
“Ground truth” cell type classification in MDS immunophenotype flow cytometry panel of 14 markers performed on samples from patients with confirmed MDS (n=118), precursor condition (CCUS, n=86), non-clonal idiopathic cytopenia of uncertain significance (ICUS, n=152) and normal controls (n=21) was performed using Infinicyt.
A neural network with an input layer accepting light scatter properties (6 channels) and fluorescent channels (8 channels) for each tube along with a tube indicator (15 total channels) followed by three fully connected hidden layers (64, 128 and 64 nodes) and an output layer including aggregates, basophils, blasts, dendritic cells, debris, granulocytes, hematogones, lymphocytes, mast cells, monocytes, plasma cells, RBCs, and unknown was trained twice on a randomly selected 80% of 353,655,369 unique events, once on uncompensated data and again with the per-tube compensated data. The uncompensated network trained to a cost of 0.16514 in 275 epochs. The compensated network reached a cost of 0.17089 after 1067 epochs. Tested on reserved data, the networks perform essentially identically, providing support to the potential clinical validity of using uncompensated data.
In this experiment, we have employed real-time ultrasound (US) imaging to determine the complete interaction between the ablation electrode and tissue to accurately estimate contact, which will help to better understand the effect of catheter pose and position relative to the tissue. By simultaneously recording tracked position, force reading and US image of the ablation catheter, the differing material properties of polyvinyl alcohol cryogel[1] phantoms are shown to produce varying amounts of tissue depression and contact area (implying varying lesion quality) for equivalent force readings. We have shown that the elastic modulus significantly affects the surface-contact area between the catheter and tissue at any level of contact force. Thus we provide evidence that a prescribed level of catheter force may not always provide sufficient contact area to produce an effective ablation lesion in the prescribed ablation time.
Semiautomatic segmentation of the heart from CT images based on intensity and morphological features
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