AIMC Topic: Image Processing, Computer-Assisted
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CACTUS: An open dataset and framework for automated Cardiac Assessment and Classification of Ultrasound images using deep transfer learning.
Computers in biology and medicine
Mar 18, 2025
Cardiac ultrasound (US) scanning is one of the most commonly used techniques in cardiology to diagnose the health of the heart and its proper functioning. During a typical US scan, medical professionals take several images of the heart to be classifi...
Deep learning-based segmentation of ultra-low-dose CT images using an optimized nnU-Net model.
La Radiologia medica
Mar 18, 2025
PURPOSE: Low-dose CT protocols are widely used for emergency imaging, follow-ups, and attenuation correction in hybrid PET/CT and SPECT/CT imaging. However, low-dose CT images often suffer from reduced quality depending on acquisition and patient att...
Stages prediction of Alzheimer's disease with shallow 2D and 3D CNNs from intelligently selected neuroimaging data.
Scientific reports
Mar 18, 2025
Detection of Alzheimer's Disease (AD) is critical for successful diagnosis and treatment, involving the common practice of screening for Mild Cognitive Impairment (MCI). However, the progressive nature of AD makes it challenging to identify its causa...
Deep image features sensing with multilevel fusion for complex convolution neural networks & cross domain benchmarks.
PloS one
Mar 18, 2025
Efficient image retrieval from a variety of datasets is crucial in today's digital world. Visual properties are represented using primitive image signatures in Content Based Image Retrieval (CBIR). Feature vectors are employed to classify images into...
Dynamic glucose enhanced imaging using direct water saturation.
Magnetic resonance in medicine
Mar 17, 2025
PURPOSE: Dynamic glucose enhanced (DGE) MRI studies employ CEST or spin lock (CESL) to study glucose uptake. Currently, these methods are hampered by low effect size and sensitivity to motion. To overcome this, we propose to utilize exchange-based li...
ECP-GAN: Generating Endometrial Cancer Pathology Images and Segmentation Labels via Two-Stage Generative Adversarial Networks.
Annals of surgical oncology
Mar 17, 2025
BACKGROUND: Endometrial cancer is one of the most common tumors of the female reproductive system and ranks third in the world list of gynecological malignancies that cause death. However, due to the privacy and complexity of pathology images, it is ...
Histopathology image classification based on semantic correlation clustering domain adaptation.
Artificial intelligence in medicine
Mar 17, 2025
Deep learning has been successfully applied to histopathology image classification tasks. However, the performance of deep models is data-driven, and the acquisition and annotation of pathological image samples are difficult, which limit the model's ...
Reduction of Acquisition Time in Fourier Transform Infrared Spectral Imaging by Deep Learning for Clinical Applications.
Analytical chemistry
Mar 17, 2025
In infrared Fourier transform spectral imaging applied to biomedical challenges, data quality is of primary importance to achieving clinical objectives. However, different noise sources affect the infrared signal coming from the sample. Generally, th...
A Two stage deep learning network for automated femoral segmentation in bilateral lower limb CT scans.
Scientific reports
Mar 17, 2025
This study presents the development of a deep learning-based two-stage network designed for the efficient and precise segmentation of the femur in full lower limb CT images. The proposed network incorporates a dual-phase approach: rapid delineation o...
Boundary-enhanced local-global collaborative network for medical image segmentation.
Scientific reports
Mar 17, 2025
Medical imaging plays a vital role as an auxiliary tool in clinical diagnosis and treatment, with segmentation serving as a crucial foundational process in medical image analysis. Nonetheless, challenges such as class imbalance and indistinct boundar...
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