A literature survey of MR-based brain tumor segmentation with missing modalities
Multimodal MR brain tumor segmentation is one of the hottest issues in the community of
medical image processing. However, acquiring the complete set of MR modalities is not …
medical image processing. However, acquiring the complete set of MR modalities is not …
Vascular implications of COVID-19: role of radiological imaging, artificial intelligence, and tissue characterization: a special report
The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people
worldwide, with mortality exceeding six million. The average survival span is just 14 days …
worldwide, with mortality exceeding six million. The average survival span is just 14 days …
[HTML][HTML] Attention-based multimodal glioma segmentation with multi-attention layers for small-intensity dissimilarity
The segmentation of glioma by computer vision is one of the hot topics in medical image
analysis, which further helps doctors to make a better treatment plan for glioma. At present …
analysis, which further helps doctors to make a better treatment plan for glioma. At present …
Attention-based UNet Deep Learning model for Plaque segmentation in carotid ultrasound for stroke risk stratification: An artificial Intelligence paradigm
Stroke and cardiovascular diseases (CVD) significantly affect the world population. The
early detection of such events may prevent the burden of death and costly surgery …
early detection of such events may prevent the burden of death and costly surgery …
[HTML][HTML] Ensemble deep learning derived from transfer learning for classification of COVID-19 patients on hybrid deep-learning-based lung segmentation: a data …
AK Dubey, GL Chabert, A Carriero, A Pasche… - Diagnostics, 2023 - mdpi.com
Background and motivation: Lung computed tomography (CT) techniques are high-
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …
A novel approach for brain tumor classification using an ensemble of deep and hand-crafted features
One of the most severe types of cancer caused by the uncontrollable proliferation of brain
cells inside the skull is brain tumors. Hence, a fast and accurate tumor detection method is …
cells inside the skull is brain tumors. Hence, a fast and accurate tumor detection method is …
Four types of multiclass frameworks for pneumonia classification and its validation in X-ray scans using seven types of deep learning artificial intelligence models
Background and Motivation: The novel coronavirus causing COVID-19 is exceptionally
contagious, highly mutative, decimating human health and life, as well as the global …
contagious, highly mutative, decimating human health and life, as well as the global …
Far wall plaque segmentation and area measurement in common and internal carotid artery ultrasound using U-series architectures: An unseen Artificial Intelligence …
Stroke risk assessment using deep learning (DL) requires automated, accurate, and real-
time risk assessment while ensuring compact model size. Previous DL paradigms suffered …
time risk assessment while ensuring compact model size. Previous DL paradigms suffered …
Clinical decision support framework for segmentation and classification of brain tumor MRIs using a U-Net and DCNN cascaded learning algorithm
Brain tumors (BTs) are an uncommon but fatal kind of cancer. Therefore, the development of
computer-aided diagnosis (CAD) systems for classifying brain tumors in magnetic …
computer-aided diagnosis (CAD) systems for classifying brain tumors in magnetic …
A systematic analysis of magnetic resonance images and deep learning methods used for diagnosis of brain tumor
S Solanki, UP Singh, SS Chouhan, S Jain - Multimedia Tools and …, 2024 - Springer
Accurate classification and segmentation of brain tumors is a critical task to perform. The
term classification is the process of grading tumors ie, whether the tumor is Malignant …
term classification is the process of grading tumors ie, whether the tumor is Malignant …