A multi-scale context aware attention model for medical image segmentation
Medical image segmentation is critical for efficient diagnosis of diseases and treatment
planning. In recent years, convolutional neural networks (CNN)-based methods, particularly …
planning. In recent years, convolutional neural networks (CNN)-based methods, particularly …
Unveiling breast cancer risk profiles: a survival clustering analysis empowered by an online web application
Aim: To develop a shiny app for doctors to investigate breast cancer treatments through a
new approach by incorporating unsupervised clustering and survival information. Materials …
new approach by incorporating unsupervised clustering and survival information. Materials …
Cheap lunch for medical image segmentation by fine-tuning sam on few exemplars
The Segment Anything Model (SAM) has demonstrated remarkable capabilities of scaled-up
segmentation models, enabling zero-shot generalization across a variety of domains. By …
segmentation models, enabling zero-shot generalization across a variety of domains. By …
Vehicle damage severity estimation for insurance operations using in-the-wild mobile images
D Mallios, L Xiaofei, N McLaughlin… - IEEE …, 2023 - ieeexplore.ieee.org
Following a car accident, an insurance company must assess the level of damage to each
vehicle to decide on the compensation paid to the insurance customer. This assessment is …
vehicle to decide on the compensation paid to the insurance customer. This assessment is …
Visual ensemble selection of deep convolutional neural networks for 3D segmentation of breast tumors on dynamic contrast enhanced MRI
M Rahimpour, MJ Saint Martin, F Frouin, P Akl… - European …, 2023 - Springer
Objectives To develop a visual ensemble selection of deep convolutional neural networks
(CNN) for 3D segmentation of breast tumors using T1-weighted dynamic contrast-enhanced …
(CNN) for 3D segmentation of breast tumors using T1-weighted dynamic contrast-enhanced …
Artificial intelligence in advancing occupational health and safety: an encapsulation of developments
Objectives: In an era characterized by dynamic technological advancements, the well-being
of the workforce remains a cornerstone of progress and sustainability. The evolving …
of the workforce remains a cornerstone of progress and sustainability. The evolving …
Cntseg: A multimodal deep-learning-based network for cranial nerves tract segmentation
The segmentation of cranial nerves (CNs) tracts based on diffusion magnetic resonance
imaging (dMRI) provides a valuable quantitative tool for the analysis of the morphology and …
imaging (dMRI) provides a valuable quantitative tool for the analysis of the morphology and …
Artificial intelligence (AI) in breast imaging: A scientometric umbrella review
Artificial intelligence (AI), a rousing advancement disrupting a wide spectrum of applications
with remarkable betterment, has continued to gain momentum over the past decades. Within …
with remarkable betterment, has continued to gain momentum over the past decades. Within …
[HTML][HTML] The role of large language models in medical image processing: a narrative review
D Tian, S Jiang, L Zhang, X Lu, Y Xu - Quantitative Imaging in …, 2024 - ncbi.nlm.nih.gov
Methods A comprehensive literature search was conducted on the Web of Science and
PubMed databases from 2013 to 2023, focusing on the transformations of LLMs in Medical …
PubMed databases from 2013 to 2023, focusing on the transformations of LLMs in Medical …
A CT-based radiomics nomogram for predicting the progression-free survival in small cell lung cancer: a multicenter cohort study
X Zheng, K Liu, C Li, C Zhu, Y Gao, J Li, X Wu - La radiologia medica, 2023 - Springer
Purpose To develop a radiomics nomogram based on computed tomography (CT) to
estimate progression-free survival (PFS) in patients with small cell lung cancer (SCLC) and …
estimate progression-free survival (PFS) in patients with small cell lung cancer (SCLC) and …