AIMC Topic: Image Processing, Computer-Assisted

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Bone shadow segmentation from ultrasound data for orthopedic surgery using GAN.

International journal of computer assisted radiology and surgery
PURPOSE: Real-time, two (2D) and three-dimensional (3D) ultrasound (US) has been investigated as a potential alternative to fluoroscopy imaging in various surgical and non-surgical orthopedic procedures. However, low signal to noise ratio, imaging ar...

Fast interactive medical image segmentation with weakly supervised deep learning method.

International journal of computer assisted radiology and surgery
PURPOSE: To achieve accurate image segmentation, which is the first critical step in medical image analysis and interventions, using deep neural networks seems a promising approach provided sufficiently large and diverse annotated data from experts. ...

Kidney segmentation from computed tomography images using deep neural network.

Computers in biology and medicine
BACKGROUND: The precise segmentation of kidneys and kidney tumors can help medical specialists to diagnose diseases and improve treatment planning, which is highly required in clinical practice. Manual segmentation of the kidneys is extremely time-co...

Keras R-CNN: library for cell detection in biological images using deep neural networks.

BMC bioinformatics
BACKGROUND: A common yet still manual task in basic biology research, high-throughput drug screening and digital pathology is identifying the number, location, and type of individual cells in images. Object detection methods can be useful for identif...

NuClick: A deep learning framework for interactive segmentation of microscopic images.

Medical image analysis
Object segmentation is an important step in the workflow of computational pathology. Deep learning based models generally require large amount of labeled data for precise and reliable prediction. However, collecting labeled data is expensive because ...

Non-ischemic endocardial scar geometric remodeling toward topological machine learning.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Scar tissues have been important factors in determining the progression of myocardial diseases and the development of adverse cardiac failure outcomes. Accurate segmentation of the scar tissues can be helpful to the clinicians for risk prediction and...

Radiomics in radiation oncology-basics, methods, and limitations.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Over the past years, the quantity and complexity of imaging data available for the clinical management of patients with solid tumors has increased substantially. Without the support of methods from the field of artificial intelligence (AI) and machin...

Radiomics in Echocardiography: Deep Learning and Echocardiographic Analysis.

Current cardiology reports
PURPOSE OF REVIEW: Recent development in artificial intelligence (AI) for cardiovascular imaging analysis, involving deep learning, is the start of a new phase in the research field. We review the current state of AI in cardiovascular field and discu...

Interactive machine learning for soybean seed and seedling quality classification.

Scientific reports
New computer vision solutions combined with artificial intelligence algorithms can help recognize patterns in biological images, reducing subjectivity and optimizing the analysis process. The aim of this study was to propose an approach based on inte...

Improved Classification of White Blood Cells with the Generative Adversarial Network and Deep Convolutional Neural Network.

Computational intelligence and neuroscience
White blood cells (leukocytes) are a very important component of the blood that forms the immune system, which is responsible for fighting foreign elements. The five types of white blood cells include , , , , and , where each type constitutes a diffe...