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T1  - Performance of a 3D convolutional neural network in the detection of hypoperfusion at CT pulmonary angiography in patients with chronic pulmonary embolism : a feasibility study 
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UR  - http://hdl.handle.net/10138/334685 
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A1  - Vainio, Tuomas J V; Mäkelä, Teemu Olavi; Savolainen, Sauli; Kangasniemi, Marko Matti 
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Y1  - 2021 
LA  - eng 
AB  - Background Chronic pulmonary embolism (CPE) is a life-threatening disease easily misdiagnosed on computed tomography. We investigated a three-dimensional convolutional neural network (CNN) algorithm for detecting hypoperfusion in CPE from computed tomography pulmonary angiography (CTPA). Methods Preoperative CTPA of 25 patients with CPE and 25 without pulmonary embolism were selected. We applied a 48%-12%-40% training-validation-testing split (12 positive and 12 negative CTPA volumes for trainin... 
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KW  - ATTENUATION; COMPUTED-TOMOGRAPHY; Computed tomography angiography; DIAGNOSIS; DISEASE; Deep learning; Feasibility Studies; HYPERTENSION; Neural networks (computer); PERFUSION; PLATFORM; Pulmonary embolism; THROMBOEMBOLISM; 114 Physical sciences 
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