RSNA Pneumonia Detection Challenge (DICOM files)

Details from the challenge: ## What am I predicting? In this challenge competitors are predicting whether pneumonia exists in a given image. They do so by predicting bounding boxes around areas of the lung. Samples without bounding boxes are negative and contain no definitive evidence of pneumonia. Samples with bounding boxes indicate evidence of pneumonia. When making predictions, competitors should predict as many bounding boxes as they feel are necessary, in the format: confidence x-min y-min width height There should be only ONE predicted row per image. This row may include multiple bounding boxes. A properly formatted row may look like any of the following. For patientIds with no predicted pneumonia / bounding boxes: 0004cfab-14fd-4e49-80ba-63a80b6bddd6, For patientIds with a single predicted bounding box: 0004cfab-14fd-4e49-80ba-63a80b6bddd6,0.5 0 0 100 100 For patientIds with multiple predicted bounding boxes: 0004cfab-14fd-4e49-80ba-63a80b6bddd6,0.5 0 0 100 100 0.5 0 0 100 100,

本挑战中，参赛者需预测给定图像中是否存在肺炎。他们通过预测肺部区域的边界框来实现这一目标。无边界框的样本为阴性，不包含肺炎的确凿证据。带有边界框的样本表明存在肺炎。在做出预测时，参赛者应预测他们认为必要的所有边界框，格式为：置信度 x-最小值 y-最小值 宽度 高度。每张图像仅应有一行预测结果。该行可能包含多个边界框。正确格式的行可能如下所示：对于无预测肺炎/边界框的患者ID：0004cfab-14fd-4e49-80ba-63a80b6bddd6，对于预测单个边界框的患者ID：0004cfab-14fd-4e49-80ba-63a80b6bddd6,0.5 0 0 100 100，对于预测多个边界框的患者ID：0004cfab-14fd-4e49-80ba-63a80b6bddd6,0.5 0 0 100 100 0.5 0 0 100 100，