Abstract: A system comprising a memory to store instructions and a processor to execute the instructions stored in the memory to receive a plurality of Computed Tomography Pulmonary Angiography (CTPA) exams as input image data, each exam in the plurality of exams comprising a varying plurality of individual images. The system annotates each of the slices with one of a pulmonary embolism (PE) present label or PE absent label, annotates each of the exams with one of a plurality of labels each indicating a different PE state and location, performs a slice-level PE classification to determine the presence or absence of PE for each of the slices, and performs and outputs, via an Embedding-based Vision Transformer (E-ViT), an exam-level diagnosis using the slice-level classifications.

Abstract: Described herein are means for systematically determining an optimal approach for the computer-aided diagnosis of a pulmonary embolism, in the context of processing medical imaging. According to a particular embodiment, there is a system specially configured for diagnosing a Pulmonary Embolism (PE) within new medical images which form no part of the dataset upon which the AI model was trained.

Abstract: Described herein are means for systematically determining an optimal approach for the computer-aided diagnosis of a pulmonary embolism, in the context of processing medical imaging. According to a particular embodiment, there is a system specially configured for diagnosing a Pulmonary Embolism (PE) within new medical images which form no part of the dataset upon which the AI model was trained.