BOA: A CT-based body and organ analysis for radiologists at the point of care
J Haubold, G Baldini, V Parmar… - Investigative …, 2023 - journals.lww.com
Purpose The study aimed to develop the open-source body and organ analysis (BOA), a
comprehensive computed tomography (CT) image segmentation algorithm with a focus on …
comprehensive computed tomography (CT) image segmentation algorithm with a focus on …
Deep learning-enabled detection of hypoxic–ischemic encephalopathy after cardiac arrest in CT scans: a comparative study of 2D and 3D approaches
NS Molinski, M Kenda, C Leithner, J Nee… - Frontiers in …, 2024 - frontiersin.org
Objective To establish a deep learning model for the detection of hypoxic–ischemic
encephalopathy (HIE) features on CT scans and to compare various networks to determine …
encephalopathy (HIE) features on CT scans and to compare various networks to determine …
Two-stage deep learning model for automated segmentation and classification of splenomegaly
Simple Summary Splenomegaly is a feature of a broad range of diseases including
hematological malignancies and non-neoplastic conditions. However, the morphological …
hematological malignancies and non-neoplastic conditions. However, the morphological …
A Deep-Learning Approach to Spleen Volume Estimation in Patients with Gaucher Disease
The enlargement of the liver and spleen (hepatosplenomegaly) is a common manifestation
of Gaucher disease (GD). An accurate estimation of the liver and spleen volumes in patients …
of Gaucher disease (GD). An accurate estimation of the liver and spleen volumes in patients …
Evaluation of manual and automated approaches for segmentation and extraction of quantitative indices from [18F] FDG PET-CT images
G Krokos, T Kotwal, A Malaih… - Biomedical physics …, 2024 - iopscience.iop.org
Utilisation of whole organ volumes to extract anatomical and functional information from
computed tomography (CT) and positron emission tomography (PET) images may provide …
computed tomography (CT) and positron emission tomography (PET) images may provide …
OPEN ACCESS EDITED BY
A Haugg, L Milosevic, DMA Mehler… - Translational …, 2024 - books.google.com
Methods: Here, we compared whole-brain activation and changes in PTSD symptoms
between PTSD participants (n= 28) that trained to downregulate activity within either the …
between PTSD participants (n= 28) that trained to downregulate activity within either the …
Fully Automated Spleen Segmentation in Patients using Convolutional Neural Network on CT Images
A deep learning network was created for the purpose of segmenting the spleen on thorax-
abdomen CT images for the purpose of this retrospective investigation. The purpose of this …
abdomen CT images for the purpose of this retrospective investigation. The purpose of this …
Automatic segmentation of intramedullary multiple sclerosis lesions delimited in DIR sequences with convolutional neural networks
P Gambús i Moreno - 2023 - repositori.upf.edu
Multiple sclerosis (MS) is a neurodegenerative disease affecting the central nervous system
(CNS), characterized by the destruction of myelin sheaths, that has become the leading …
(CNS), characterized by the destruction of myelin sheaths, that has become the leading …
[PDF][PDF] A Deep Neural Network Approach on Spleen Cancer Detection using DenseNet-201
N Nazir, RP Singh, M Mehra - academia.edu
Spleen is the largest secondary lymphoid organ and play a crucial role in the regulation of
innate and adaptive immune. Among all cancers, spleen cancer is one of the serious …
innate and adaptive immune. Among all cancers, spleen cancer is one of the serious …