AIMC Topic: Image Processing, Computer-Assisted

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Current Advances in Computational Lung Ultrasound Imaging: A Review.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In the field of biomedical imaging, ultrasonography has become common practice, and used as an important auxiliary diagnostic tool with unique advantages, such as being non-ionizing and often portable. This article reviews the state-of-the-art in med...

Ultrasound Signal Processing: From Models to Deep Learning.

Ultrasound in medicine & biology
Medical ultrasound imaging relies heavily on high-quality signal processing to provide reliable and interpretable image reconstructions. Conventionally, reconstruction algorithms have been derived from physical principles. These algorithms rely on as...

Cervical cell classification with deep-learning algorithms.

Medical & biological engineering & computing
Cervical cancer is a serious threat to the lives and health of women. The accurate analysis of cervical cell smear images is an important diagnostic basis for cancer identification. However, pathological data are often complex and difficult to analyz...

An end-end deep learning framework for lesion segmentation on multi-contrast MR images-an exploratory study in a rat model of traumatic brain injury.

Medical & biological engineering & computing
Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra-areas of secondary neural injury which are crucial targets for therapeutic interventions. Segmenting manually areas of ongoing changes like necrosis, edema, hematoma, and inflamma...

Reinforcement learning in medical image analysis: Concepts, applications, challenges, and future directions.

Journal of applied clinical medical physics
MOTIVATION: Medical image analysis involves a series of tasks used to assist physicians in qualitative and quantitative analyses of lesions or anatomical structures which can significantly improve the accuracy and reliability of medical diagnoses and...

Tongue crack recognition using segmentation based deep learning.

Scientific reports
Tongue cracks refer to fissures with different depth and shapes on the tongue's surface, which can characterize the pathological characteristics of spleen and stomach. Tongue cracks are of great significance to the objective study of tongue diagnosis...

Comparison of image quality of two versions of deep-learning image reconstruction algorithm on a rapid kV-switching CT: a phantom study.

European radiology experimental
BACKGROUND: To assess the impact of the new version of a deep learning (DL) spectral reconstruction on image quality of virtual monoenergetic images (VMIs) for contrast-enhanced abdominal computed tomography in the rapid kV-switching platform.

Automated multi-modal Transformer network (AMTNet) for 3D medical images segmentation.

Physics in medicine and biology
Over the past years, convolutional neural networks based methods have dominated the field of medical image segmentation. But the main drawback of these methods is that they have difficulty representing long-range dependencies. Recently, the Transform...

Democratization of deep learning for segmenting cartilage from MRIs of human knees: Application to data from the osteoarthritis initiative.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
In this study, we aimed to democratize access to convolutional neural networks (CNN) for segmenting cartilage volumes, generating state-of-the-art results for specialized, real-world applications in hospitals and research. Segmentation of cross-secti...

Developing a Novel Methodology by Integrating Deep Learning and HMM for Segmentation of Retinal Blood Vessels in Fundus Images.

Interdisciplinary sciences, computational life sciences
Accurate segregation of retinal blood vessels network plays a crucial role in clinical assessments, treatments, and rehabilitation process. Owing to the presence of acquisition and instrumentation anomalies, precise tracking of vessels network is cha...