AIMC Topic: Image Processing, Computer-Assisted

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Deep learning enables fast and dense single-molecule localization with high accuracy.

Nature methods
Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but standard analysis algorithms require sparse emitters, which limits imaging speed and labeling density. Here, we ov...

Method of Tumor Pathological Micronecrosis Quantification Via Deep Learning From Label Fuzzy Proportions.

IEEE journal of biomedical and health informatics
The presence of necrosis is associated with tumor progression and patient outcomes in many cancers, but existing analyses rarely adopt quantitative methods because the manual quantification of histopathological features is too expensive. We aim to ac...

Learning a Deep CNN Denoising Approach Using Anatomical Prior Information Implemented With Attention Mechanism for Low-Dose CT Imaging on Clinical Patient Data From Multiple Anatomical Sites.

IEEE journal of biomedical and health informatics
Dose reduction in computed tomography (CT) has gained considerable attention in clinical applications because it decreases radiation risks. However, a lower dose generates noise in low-dose computed tomography (LDCT) images. Previous deep learning (D...

SFPD: Simultaneous Face and Person Detection in Real-Time for Human-Robot Interaction.

Sensors (Basel, Switzerland)
Face and person detection are important tasks in computer vision, as they represent the first component in many recognition systems, such as face recognition, facial expression analysis, body pose estimation, face attribute detection, or human action...

DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels.

eLife
Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored manually, which is time-consuming, limited to few ...

Multi-feature data repository development and analytics for image cosegmentation in high-throughput plant phenotyping.

PloS one
Cosegmentation is a newly emerging computer vision technique used to segment an object from the background by processing multiple images at the same time. Traditional plant phenotyping analysis uses thresholding segmentation methods which result in h...

A CNN-based method to reconstruct 3-D spine surfaces from US images in vivo.

Medical image analysis
Three-dimensional (3-D) reconstruction of the spine surface is of strong clinical relevance for the diagnosis and prognosis of spine disorders and intra-operative image guidance. In this paper, we report a new technique to reconstruct lumbar spine su...

Simultaneous Segmentation of Fetal Hearts and Lungs for Medical Ultrasound Images via an Efficient Multi-scale Model Integrated With Attention Mechanism.

Ultrasonic imaging
Large scale early scanning of fetuses via ultrasound imaging is widely used to alleviate the morbidity or mortality caused by congenital anomalies in fetal hearts and lungs. To reduce the intensive cost during manual recognition of organ regions, man...

Learning Dynamic Textures for Neural Rendering of Human Actors.

IEEE transactions on visualization and computer graphics
Synthesizing realistic videos of humans using neural networks has been a popular alternative to the conventional graphics-based rendering pipeline due to its high efficiency. Existing works typically formulate this as an image-to-image translation pr...