AIMC Topic: Image Processing, Computer-Assisted

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Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages.

Scientific reports
Cerebral microhemorrhages (CMHs) are associated with cerebrovascular disease, cognitive impairment, and normal aging. One method to study CMHs is to analyze histological sections (5-40 μm) stained with Prussian blue. Currently, users manually and sub...

Analysing wideband absorbance immittance in normal and ears with otitis media with effusion using machine learning.

Scientific reports
Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation of WAI results. This study aimed to develop Machine Learning (ML) too...

Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography.

Nature communications
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population. Low dose computed tomography (LDCT) for lung cancer screening offers an opportunity for simultaneous CVD risk estimation in at-risk patients. Ou...

Segmenting lung lesions of COVID-19 from CT images via pyramid pooling improved Unet.

Biomedical physics & engineering express
Segmenting lesion regions of Coronavirus Disease 2019 (COVID-19) from computed tomography (CT) images is a challenge owing to COVID-19 lesions characterized by high variation, low contrast between infection lesions and around normal tissues, and blur...

Pancreas segmentation with probabilistic map guided bi-directional recurrent UNet.

Physics in medicine and biology
Pancreas segmentation in medical imaging is of great significance for clinical pancreas diagnostics and treatment. However, the large population variations in the pancreas shape and volume cause enormous segmentation difficulties, even for state-of-t...

High-frequency conductivity at Larmor-frequency in human brain using moving local window multilayer perceptron neural network.

PloS one
Magnetic resonance electrical properties tomography (MREPT) aims to visualize the internal high-frequency conductivity distribution at Larmor frequency using the B1 transceive phase data. From the magnetic field perturbation by the electrical field a...

Automatic cervical lymphadenopathy segmentation from CT data using deep learning.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to develop a fast and automatic algorithm to detect and segment lymphadenopathy from head and neck computed tomography (CT) examination.

MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning.

Medical image analysis
Segmentation of organs or lesions from medical images plays an essential role in many clinical applications such as diagnosis and treatment planning. Though Convolutional Neural Networks (CNN) have achieved the state-of-the-art performance for automa...

MRI and CT bladder segmentation from classical to deep learning based approaches: Current limitations and lessons.

Computers in biology and medicine
Precise determination and assessment of bladder cancer (BC) extent of muscle invasion involvement guides proper risk stratification and personalized therapy selection. In this context, segmentation of both bladder walls and cancer are of pivotal impo...