AIMC Topic: Image Processing, Computer-Assisted

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Multi-view hybrid encoder U-Net for 3D renal vascular medical image segmentation.

Scientific reports
Understanding the size, shape, branching angles, and morphological features of blood vessels in human tissue remains challenging. To address this, we propose a multi-view hybrid encoder U-Net for segmenting renal artery vessels. The encoder in this m...

GTV segmentation in MRI guided radiotherapy with promptable foundation models.

Physics in medicine and biology
. Magnetic resonance imaging (MRI) guided radiotherapy requires the delineation of gross tumor volumes (GTV) in daily MRI from MRI-linacs. Specialized models have been developed for this task for certain tumors. This study investigated an alternative...

SDMFFN: a novel specular detection median filtering fusion network for specular reflection removal in endoscopic images.

Biomedical physics & engineering express
. Endoscopic imaging is vital in Minimally Invasive Surgery (MIS), but its utility is often compromised by specular reflections that obscure important details and hinder diagnostic accuracy. Existing methods to address these reflections face limitati...

Enhanced sentiment analysis in tourism reviews via multimodal graph convolutional networks.

PloS one
In recent years, multimodal sentiment analysis has gained prominence due to its ability to leverage diverse data types for improved accuracy. However, combining text and image modalities presents challenges in effectively integrating and processing t...

Reinforcement learning for medical image analysis: a systematic review of algorithms, engineering challenges, and clinical deployment.

Computer assisted surgery (Abingdon, England)
Reinforcement learning (RL) has emerged as a powerful artificial intelligence paradigm in medical image analysis, excelling in complex decision-making tasks. This systematic review synthesizes the applications of RL across diverse imaging domains-inc...

Subtype classification of gastric spindle cell tumors in whole slide images.

Computers in biology and medicine
AIMS: Accurate cancer subtype classification is critical due to variations in tumor progression and prognosis. Traditionally, pathologists classified subtypes manually by examining pathological slides under the microscope. To address increasing workl...

Enhanced classification prostate cancer based on generative adversarial networks and integrated deep learning with vision transformer models.

Scientific reports
By eliminating the need to alter the source images, this paper introduces a secure technique for coverless image steganography that strengthens defense against steganalysis attacks. Our method makes use of a hybrid Generative Adversarial Network (GAN...

Pattern and structural detection in grayscale images through the application of quantile graphs in higher-dimensional spaces.

Scientific reports
Deep Learning (DL) and Machine Learning (ML) algorithms are adept at managing and classifying a wide range of data formats, including time series, text, and images, addressing challenges in both supervised and unsupervised learning. However, the prac...

Comparative analysis of retinal and cerebral vascular responses to CO₂ using Doppler optical coherence tomography and transcranial Doppler ultrasound.

Physics in medicine and biology
Access to blood flow data in cerebral and retinal vascular beds is crucial for diagnosing cerebrovascular diseases. This study addresses two technological gaps: (1) simultaneous recording of vascular responses in the brain and eye by integrating tran...

SSMCE: A semi-supervised learning framework for myocardial segmentation in myocardial contrast echocardiography.

Biomedical physics & engineering express
Accurate myocardial segmentation in myocardial contrast echocardiography (MCE) images remains challenging due to the scarcity of publicly available labeled datasets and the pervasive presence of speckle noise.Currently, echocardiographers must manual...