Background: Classification of optical coherence tomography (OCT) images can be achieved with high accuracy using classical convolution neural networks (CNN), a commonly used deep learning network for computer-aided diagnosis. Classical CNN has often been criticized for suppressing positional relations in a pooling layer. Therefore, because capsule networks can learn positional information from images, we attempted application of a capsule network to OCT images to overcome that shortcoming. This study is our attempt to improve classification accuracy by replacing CNN with a capsule network. Methods: From an OCT dataset, we produced a training dataset of 83,484 images and a test dataset of 1000 images. For training, the dataset comprises 37,205 images with choroidal neovascularization (CNV), 11,348 with diabetic macular edema (DME), 8616 with drusen, and 26,315 normal images. The test dataset has 250 images from each category. The proposed model was constructed based on a capsule network for improving classification accuracy. It was trained using the training dataset. Subsequently, the test dataset was used to evaluate the trained model.Results: Classification of OCT images using our method achieved accuracy of 99.6%, which is 3.2 percentage points higher than that of other methods described in the literature. Conclusion: The proposed method achieved classification accuracy results equivalent to those reported for other methods for CNV, DME, drusen, and normal images.
The catalytic enantioselective oxidative hetero-coupling of arenols using a chiral vanadium(v) complex has been developed. The coupling of hydroxycarbazole derivatives with various arenols provided axially chiral biarenols in high chemo-,...
SUMMARYUmbilical cord blood (CB) has been widely used instead of bone marrow (BM) and peripheral blood (PB) for stem cell transplantation (SCT). However, problems of sustained immunode®ciency after CB transplantation remain to be resolved. To elucidate the mechanism of immunode®ciency, we compared the characteristics of B cells differentiated in vitro from CD34+ cells of CB with those of PB. Puri®ed CD34+ cells from CB and PB were cultured on murine stroma cell-line MS-5 with stem cell factor and granulocyte colony-stimulating factor for 6 weeks. The B-cell precursors (pre-B cells) that differentiated in this culture system, were analysed as to their immunoglobulin heavy chain (IgH) variable region gene repertoire and the expression of B-cell differentiation-related genes. CD10 + CD19 + pre-B cells were differentiated from both PB and CB. Although the usages of IgH gene segments in pre-B cells differentiated from CB and PB were similar, the N region was signi®cantly shorter in CB-derived than PB-derived cells. Productive rearrangements were signi®cantly fewer in cells of CB than PB in the third week. Among a number of B-cell differentiation-related genes, the terminal deoxynucleotidyl transferase (TdT) gene was not expressed in CB-derived cells during the culture. These results indicated that immature features of pre-B cells from CB, such as lack of TdT expression, and a short N region and few productive rearrangements in the IgH gene, might cause the delay in mature B-cell production.
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