AIMC Topic: Image Processing, Computer-Assisted

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Rapid Quality Assessment of Nonrigid Image Registration Based on Supervised Learning.

Journal of digital imaging
When preprocedural images are overlaid on intraprocedural images, interventional procedures benefit in that more structures are revealed in intraprocedural imaging. However, image artifacts, respiratory motion, and challenging scenarios could limit t...

Deep embeddings and logistic regression for rapid active learning in histopathological images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Recognizing different tissue components is one of the most fundamental and essential works in digital pathology. Current methods are often based on convolutional neural networks (CNNs), which need numerous annotated samples ...

MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning.

Nature communications
Understanding the basis of brain function requires knowledge of cortical operations over wide spatial scales and the quantitative analysis of brain activity in well-defined brain regions. Matching an anatomical atlas to brain functional data requires...

BCHisto-Net: Breast histopathological image classification by global and local feature aggregation.

Artificial intelligence in medicine
Breast cancer among women is the second most common cancer worldwide. Non-invasive techniques such as mammograms and ultrasound imaging are used to detect the tumor. However, breast histopathological image analysis is inevitable for the detection of ...

COVID-19 Diagnosis from CT Images with Convolutional Neural Network Optimized by Marine Predator Optimization Algorithm.

BioMed research international
In recent years, almost every country in the world has struggled against the spread of Coronavirus Disease 2019. If governments and public health systems do not take action against the spread of the disease, it will have a severe impact on human life...

Estimating subjective evaluation of low-contrast resolution using convolutional neural networks.

Physical and engineering sciences in medicine
To develop a convolutional neural network-based method for the subjective evaluation of computed tomography (CT) images having low-contrast resolution due to imaging conditions and nonlinear image processing. Four radiological technologists visually ...

Global processing provides malignancy evidence complementary to the information captured by humans or machines following detailed mammogram inspection.

Scientific reports
The information captured by the gist signal, which refers to radiologists' first impression arising from an initial global image processing, is poorly understood. We examined whether the gist signal can provide complementary information to data captu...

CST: A Multitask Learning Framework for Colorectal Cancer Region Mining Based on Transformer.

BioMed research international
Colorectal cancer is a high death rate cancer until now; from the clinical view, the diagnosis of the tumour region is critical for the doctors. But with data accumulation, this task takes lots of time and labor with large variances between different...