A comprehensive review and experimental comparison of deep learning methods for automated hemorrhage detection
Hemorrhagic stroke poses a critical medical emergency that necessitates prompt and
accurate diagnosis to prevent irreversible brain damage. The emergence of automated deep …
accurate diagnosis to prevent irreversible brain damage. The emergence of automated deep …
Quadratic Convolution-based YOLOv8 (Q-YOLOv8) for localization of intracranial hemorrhage from head CT images
Intracranial hemorrhage (ICH) is a stroke type with very high morbidity and mortality rates.
This kind of disease requires an early and rapid diagnosis via computed tomography (CT) …
This kind of disease requires an early and rapid diagnosis via computed tomography (CT) …
YOLOv5s-CAM: A deep learning model for automated detection and classification for types of intracranial hematoma in CT images
Intracranial hematoma due to traumatic brain injury is a serious health concern with rates of
morbidity and mortality that are increasing worldwide. Manual identification is slow, subject …
morbidity and mortality that are increasing worldwide. Manual identification is slow, subject …
An attention-based ResNet architecture for acute hemorrhage detection and classification: Toward a health 4.0 digital twin study
Due to the advancement of digital twin (DT) technology, Health 4.0 applications have
become reality and starting to take roots. In this article, we focus on intracranial hemorrhage …
become reality and starting to take roots. In this article, we focus on intracranial hemorrhage …
Weakly supervised intracranial hemorrhage segmentation using head-wise gradient-infused self-attention maps from a swin transformer in categorical learning
Intracranial hemorrhage (ICH) is a life-threatening medical emergency that requires timely
and accurate diagnosis for effective treatment and improved patient survival rates. While …
and accurate diagnosis for effective treatment and improved patient survival rates. While …
Weakly supervised intracranial hemorrhage segmentation using hierarchical combination of attention maps from a swin transformer
Intracranial hemorrhage (ICH) is a potentially life-threatening emergency due to various
causes. Rapid and accurate diagnosis of ICH is critical to deliver timely treatments and …
causes. Rapid and accurate diagnosis of ICH is critical to deliver timely treatments and …
Automatic hemorrhage detection from color Doppler ultrasound using a Generative Adversarial Network (GAN)-based anomaly detection method
Hemorrhage control has been identified as a priority focus area both for civilian and military
populations in the United States because exsanguination is the most common cause of …
populations in the United States because exsanguination is the most common cause of …
Intracranial hematoma segmentation on head CT based on multiscale convolutional neural network and transformer
G Li, K Gao, C Liu, S Li - IET Image Processing, 2024 - Wiley Online Library
Intracranial hematoma, a severe brain injury caused by trauma or cerebrovascular disease,
can result in blood accumulation and compression of brain tissue. Untreated cases can …
can result in blood accumulation and compression of brain tissue. Untreated cases can …
Weakly Supervised Intracranial Hemorrhage Segmentation with YOLO and an Uncertainty Rectified Segment Anything Model
Intracranial hemorrhage (ICH) is a life-threatening condition that requires rapid and accurate
diagnosis to improve treatment outcomes and patient survival rates. Recent advancements …
diagnosis to improve treatment outcomes and patient survival rates. Recent advancements …
Class Activation Map-based Weakly supervised Hemorrhage Segmentation using Resnet-LSTM in Non-Contrast Computed Tomography images
SH Ramananda, V Sundaresan - arXiv preprint arXiv:2309.16627, 2023 - arxiv.org
In clinical settings, intracranial hemorrhages (ICH) are routinely diagnosed using non-
contrast CT (NCCT) for severity assessment. Accurate automated segmentation of ICH …
contrast CT (NCCT) for severity assessment. Accurate automated segmentation of ICH …