AIMC Topic: Image Processing, Computer-Assisted

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Fully transformer network for skin lesion analysis.

Medical image analysis
Automatic skin lesion analysis in terms of skin lesion segmentation and disease classification is of great importance. However, these two tasks are challenging as skin lesion images of multi-ethnic population are collected using various scanners in m...

TransDIR: Deformable imaging registration network based on transformer to improve the feature extraction ability.

Medical physics
PURPOSE: Imaging registration has a significant contribution to guide and support physicians in the process of decision-making for diagnosis, prognosis, and treatment. However, existing registration methods based on the convolutional neural network c...

CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images.

BMC bioinformatics
BACKGROUND: Algorithmic cellular segmentation is an essential step for the quantitative analysis of highly multiplexed tissue images. Current segmentation pipelines often require manual dataset annotation and additional training, significant paramete...

DeLTA 2.0: A deep learning pipeline for quantifying single-cell spatial and temporal dynamics.

PLoS computational biology
Improvements in microscopy software and hardware have dramatically increased the pace of image acquisition, making analysis a major bottleneck in generating quantitative, single-cell data. Although tools for segmenting and tracking bacteria within ti...

Microscopic retinal blood vessels detection and segmentation using support vector machine and K-nearest neighbors.

Microscopy research and technique
The retina is the deepest layer of texture covering the rear of the eye, recorded by fundus images. Vessel detection and segmentation are useful in disease diagnosis. The retina's blood vessels could help diagnose maladies such as glaucoma, diabetic ...

Segmenting pediatric optic pathway gliomas from MRI using deep learning.

Computers in biology and medicine
Optic pathway gliomas are low-grade neoplastic lesions that account for approximately 3-5% of brain tumors in children. Assessing tumor burden from magnetic resonance imaging (MRI) plays a central role in its efficient management, yet it is a challen...

Intelligent Semantic Segmentation for Self-Driving Vehicles Using Deep Learning.

Computational intelligence and neuroscience
Understanding the situation is a critical component of any self-driving system. Accurate real-time visual signal processing to create pixelwise classed pictures, also known as semantic segmentation, is critical for scenario comprehension and subseque...

Rubik-Net: Learning Spatial Information via Rotation-Driven Convolutions for Brain Segmentation.

IEEE journal of biomedical and health informatics
The accurate segmentation of brain tissue in Magnetic Resonance Image (MRI) slices is essential for assessing neurological conditions and brain diseases. However, it is challenging to segment MRI slices because of the low contrast between different b...

Joint Optimization of CycleGAN and CNN Classifier for Detection and Localization of Retinal Pathologies on Color Fundus Photographs.

IEEE journal of biomedical and health informatics
Retinal related diseases are the leading cause of vision loss, and severe retinal lesion causes irreversible damage to vision. Therefore, the automatic methods for retinal diseases detection based on medical images is essential for timely treatment. ...

A Large-Scale Dataset and Deep Learning Model for Detecting and Counting Olive Trees in Satellite Imagery.

Computational intelligence and neuroscience
Since the Pre-Roman era, olive trees have a significant economic and cultural value. In 2019, the Al-Jouf region, in the north of the Kingdom of Saudi Arabia, gained a global presence by entering the Guinness World Records, with the largest number of...