The model consists of a modified Resnet50 backbone for extracting feature corpus from the images, a classifier, and a pixel correlation module (PCM). This paper proposes a deep learning model for the classification and localization of chest diseases by using image-level annotations. Therefore, there is a drift toward developing computer-aided assistive systems to help radiologists. However, close to fourteen commonly occurring diseases are sometimes difficult to identify by visually inspecting the images.
Therefore, a 2D view of the 3D anatomy is sometimes sufficient for the initial diagnosis. Learn more about relative units here.Chest X-Ray (CXR) images provide most anatomical details and the abnormalities on a 2D plane. You can change the units from the default (pixels) to percentage, em, rem, vw, and vh. Letter spacing sets the space between each character of the text. Letter case allows you to set the text to all caps, the first letter capitalized, or all lower case. If you select zero, be sure to check your site on mobile.ĭecoration includes options for underline and strikethrough (if available.)
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Choose from a list of fonts in a drop-down menu.Īppearance allows you to change the text’s style between regular and italic, ranging from thin to extra bold.
Choices are pixels, em or rem.įont family gives you the option to change the font style used. You can change the units by clicking where a number 2 is marked in the screenshot below. You can also set a specific value by clicking the slider icon directly above the default selections, marked with a 1 in the screenshot below. You can choose from preset sizes like small, medium, and large. Typography in the Block Settings sidebar, with the additional options expanded.įont size allows you to adjust the size of the text.
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