TRAINING APPARATUS, METHOD, AND IMAGE PROCESSING APPARATUS

原文（中文）

According to one embodiment, a training apparatus includes processing circuitry. The processing circuitry calculates a similarity between a subject image and at least one normal image. The processing circuitry selects at least one reference image from the normal image based on the similarity. The processing circuitry calculates first feature maps of the subject image and second feature maps of the reference image using a first machine learning model. The processing circuitry calculates differential feature maps that are differences between the first and second feature maps. The processing circuitry calculates a likelihood map based on the first feature maps and the differential feature maps using a second machine learning model. The processing circuitry calculates, based on the likelihood map and a teaching label of the subject image, a loss based on a likelihood. The processing circuitry updates the first and second machine learning models based on the loss.