"Liver blood clot:" A reactionary hemorrhage following periodontal surgery
Contemporary Clinical Dentistry, 2014 Invasive dental procedures, such as extractions and periodontal surgeries, are associated with postoperative bleeding, which is generally self-arresting.
J Barot Varshal
doaj +1 more source
An Effective Transformer-based Solution for RSNA Intracranial Hemorrhage Detection Competition [PDF]
arXiv, 2022 We present an effective method for Intracranial Hemorrhage Detection (IHD) which exceeds the performance of the winner solution in RSNA-IHD competition (2019). Meanwhile, our model only takes quarter parameters and ten percent FLOPs compared to the winner's solution.
arxiv
Treatment Outcome Prediction for Intracerebral Hemorrhage via Generative Prognostic Model with Imaging and Tabular Data [PDF]
arXiv, 2023 Intracerebral hemorrhage (ICH) is the second most common and deadliest form of stroke. Despite medical advances, predicting treat ment outcomes for ICH remains a challenge. This paper proposes a novel prognostic model that utilizes both imaging and tabular data to predict treatment outcome for ICH.
arxiv
BHSD: A 3D Multi-Class Brain Hemorrhage Segmentation Dataset [PDF]
arXiv, 2023 Intracranial hemorrhage (ICH) is a pathological condition characterized by bleeding inside the skull or brain, which can be attributed to various factors. Identifying, localizing and quantifying ICH has important clinical implications, in a bleed-dependent manner.
arxiv
Is This Contrast? Is This Blood? An Agreement Study on Post-thrombectomy Computed Tomography Scans
Frontiers in Neurology, 2020 Background: Hemorrhagic transformation after acute ischemic stroke is a dreaded and severe complication of thrombolysis and thrombectomy. However, its detection on post-thrombectomy conventional non-contrast computed tomography (CT) scan can be ...
Ronda Lun +16 more
doaj +1 more source
Application of Deep Learning in Neuroradiology: Automated Detection of Basal Ganglia Hemorrhage using 2D-Convolutional Neural Networks [PDF]
arXiv, 2017 Background: Deep learning techniques have achieved high accuracy in image classification tasks, and there is interest in applicability to neuroimaging critical findings. This study evaluates the efficacy of 2D deep convolutional neural networks (DCNNs) for detecting basal ganglia (BG) hemorrhage on noncontrast head CT.
arxiv
Hemorrhagic Endovasculitis and Hemorrhagic Villitis of the Placenta
Obstetrical & Gynecological Survey, 1981 A unique vascular lesion has been identified in 32 placentas sent to the Michigan Placental Tissue Registry, East Lansing, Mich. Half of the associated infants are stillborn; 11 of 16 liveborn were in distress or small for gestational age. Placental vessels show thrombosis, endothelial, and medial hyperplasia and narrowing or obliteration of the lumen.
openaire +3 more sources
Intracranial Hemorrhage Detection Using Neural Network Based Methods With Federated Learning [PDF]
arXiv, 2020 Intracranial hemorrhage, bleeding that occurs inside the cranium, is a serious health problem requiring rapid and often intensive medical treatment. Such a condition is traditionally diagnosed by highly-trained specialists analyzing computed tomography (CT) scan of the patient and identifying the location and type of hemorrhage if one exists.
arxiv
A CNN-LSTM Architecture for Detection of Intracranial Hemorrhage on CT scans [PDF]
arXiv, 2020 We propose a novel method that combines a convolutional neural network (CNN) with a long short-term memory (LSTM) mechanism for accurate prediction of intracranial hemorrhage on computed tomography (CT) scans. The CNN plays the role of a slice-wise feature extractor while the LSTM is responsible for linking the features across slices.
arxiv