Radiographic Dataset for VHS determination learning process
The data collected at baseline include latero lateral thoracic radiographic images of canine patients. This data was collected in 2019- 2020. The number of patients is 156 canine patients. The dataset consists of 156 radiographic images . The images are in PNG format. Materials and Methods Radiograp...
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Zusammenfassung: | The data collected at baseline include latero lateral thoracic radiographic images of canine patients. This data was collected in 2019- 2020. The number of patients is 156 canine patients. The dataset consists of 156 radiographic images . The images are in PNG format. Materials and Methods Radiographic images were taken and collected at the Small Animal Veterinary Teaching Hospital, Veterinary Sciences Reasearch Institute, Autonomous University of Baja California. The image collection and classification was performed between 2019- 2020. The instrument used in the radiographic image adquisition process is Universal AV Choice X-Ray System and Rayence XMARU 1417PGA-PCA 14×17″ cassette digital detector (DR system). In the development of radiographic studies, techniques were used in the range of the following parameters using a high peak kilovoltage (kVp 70-80) and low milliampere-second technique (mA 200, ms 10-40) equivalent to 2-8 mAs. This technique allows for latitude (long gray scale) images, which are important when evaluating the structures of the thorax. For a right and left lateral image, patients were positioned on the table with the dependent side down. Relevant anatomical structures in the determination of VHS were included. The laterals beam projections extended from the cranial margin of the manubrium to the caudo-dorsal margin of the lung margin/diaphragmatic crus. The sternum of the patient was included so as not to exclude vital anatomy. The number of images collected initially was 628 and were stored in a DICOM format. DICOM images were converted to PNG format by using a DICOM converter application included on the acquisition software. After performing classification and preprocessing, the number of images included in the final dataset was reduced to 152 representative images. All images were cropped to different sizes to remove unused and unimportant boundaries from the images using fast photo crop. As the original images contain confidential patient information not relevant for the overall educational purpose, the data was anonymized by removing all fields that would enable patient identification. The original VHS measurement was not included in the image because they may affect the output results of the training process. |
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DOI: | 10.17632/ktx4cj55pn.1 |