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- Rajamani, Srividya Tirunellai, et al.
(författare)
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Toward Detecting and Addressing Corner Cases in Deep Learning Based Medical Image Segmentation
- 2023
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Ingår i: IEEE Access. - 2169-3536. ; 11, s. 95334-95345
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Tidskriftsartikel (refereegranskat)abstract
- Translating machine learning research into clinical practice has several challenges. In this paper, we identify some critical issues in translating research to clinical practice in the context of medical image segmentation and propose strategies to systematically address these challenges. Specifically, we focus on cases where the model yields erroneous segmentation, which we define as corner cases. One of the standard metrics used for reporting the performance of medical image segmentation algorithms is the average Dice score across all patients. We have discovered that this aggregate reporting has the inherent drawback that the corner cases where the algorithm or model has erroneous performance or very low metrics go unnoticed. Due to this reporting, models that report superior performance could end up producing completely erroneous results, or even anatomically impossible results in a few challenging cases, albeit without being noticed.We have demonstrated how corner cases go unnoticed using the Magnetic Resonance (MR) cardiac image segmentation task of the Automated Cardiac Diagnosis Challenge (ACDC) challenge. To counter this drawback, we propose a framework that helps to identify and report corner cases. Further, we propose a novel balanced checkpointing scheme capable of finding a solution that has superior performance even on these corner cases. Our proposed scheme leads to an improvement of 44.6% for LV, 46.1% for RV and 38.1% for the Myocardium on our identified corner case in the ACDC segmentation challenge. Further, we establish the generalisability of our proposed framework by also demonstrating its applicability in the context of chest X-ray lung segmentation. This framework has broader applications across multiple deep learning tasks even beyond medical image segmentation.
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| 2. |
- Marto, João Pedro, et al.
(författare)
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Safety and Outcome of Revascularization Treatment in Patients With Acute Ischemic Stroke and COVID-19: The Global COVID-19 Stroke Registry.
- 2023
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Ingår i: Neurology. - 1526-632X. ; 100:7
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Tidskriftsartikel (refereegranskat)abstract
- COVID-19-related inflammation, endothelial dysfunction, and coagulopathy may increase the bleeding risk and lower the efficacy of revascularization treatments in patients with acute ischemic stroke (AIS). We aimed to evaluate the safety and outcomes of revascularization treatments in patients with AIS and COVID-19.This was a retrospective multicenter cohort study of consecutive patients with AIS receiving intravenous thrombolysis (IVT) and/or endovascular treatment (EVT) between March 2020 and June 2021 tested for severe acute respiratory syndrome coronavirus 2 infection. With a doubly robust model combining propensity score weighting and multivariate regression, we studied the association of COVID-19 with intracranial bleeding complications and clinical outcomes. Subgroup analyses were performed according to treatment groups (IVT-only and EVT).Of a total of 15,128 included patients from 105 centers, 853 (5.6%) were diagnosed with COVID-19; of those, 5,848 (38.7%) patients received IVT-only and 9,280 (61.3%) EVT (with or without IVT). Patients with COVID-19 had a higher rate of symptomatic intracerebral hemorrhage (SICH) (adjusted OR 1.53; 95% CI 1.16-2.01), symptomatic subarachnoid hemorrhage (SSAH) (OR 1.80; 95% CI 1.20-2.69), SICH and/or SSAH combined (OR 1.56; 95% CI 1.23-1.99), 24-hour mortality (OR 2.47; 95% CI 1.58-3.86), and 3-month mortality (OR 1.88; 95% CI 1.52-2.33). Patients with COVID-19 also had an unfavorable shift in the distribution of the modified Rankin score at 3 months (OR 1.42; 95% CI 1.26-1.60).Patients with AIS and COVID-19 showed higher rates of intracranial bleeding complications and worse clinical outcomes after revascularization treatments than contemporaneous non-COVID-19 patients receiving treatment. Current available data do not allow direct conclusions to be drawn on the effectiveness of revascularization treatments in patients with COVID-19 or to establish different treatment recommendations in this subgroup of patients with ischemic stroke. Our findings can be taken into consideration for treatment decisions, patient monitoring, and establishing prognosis.The study was registered under ClinicalTrials.gov identifier NCT04895462.
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