AIMC Topic: Image Processing, Computer-Assisted

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Contour proposal networks for biomedical instance segmentation.

Medical image analysis
We present a conceptually simple framework for object instance segmentation, called Contour Proposal Network (CPN), which detects possibly overlapping objects in an image while simultaneously fitting closed object contours using a fixed-size represen...

Automatic quantitative evaluation of normal pancreas based on deep learning in a Chinese adult population.

Abdominal radiology (New York)
OBJECTIVE: To develop a 3D U-Net-based model for the automatic segmentation of the pancreas using the diameters, volume, and density of normal pancreases among Chinese adults.

Sub-micro scale cell segmentation using deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Automated cell segmentation is key for rapid and accurate investigation of cell responses. As instrumentation resolving power increases, clear delineation of newly revealed cellular features at the submicron through nanoscale becomes important. Relia...

High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.

European radiology
OBJECTIVES: To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26 kg/m,...

A multi-task two-path deep learning system for predicting the invasiveness of craniopharyngioma.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Craniopharyngioma is a kind of benign brain tumor in histography. However, it might be clinically aggressive and have severe manifestations, such as increased intracranial pressure, hypothalamic-pituitary dysfunction, and vi...

Inpainted Image Reconstruction Using an Extended Hopfield Neural Network Based Machine Learning System.

Sensors (Basel, Switzerland)
This paper considers the use of a machine learning system for the reconstruction and recognition of distorted or damaged patterns, in particular, images of faces partially covered with masks. The most up-to-date image reconstruction structures are ba...

A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm.

Scientific reports
Accurate and early detection of anomalies in peripheral white blood cells plays a crucial role in the evaluation of well-being in individuals and the diagnosis and prognosis of hematologic diseases. For example, some blood disorders and immune system...

Intelligent fluorescence image analysis of giant unilamellar vesicles using convolutional neural network.

BMC bioinformatics
BACKGROUND: Fluorescence image analysis in biochemical science often involves the complex tasks of identifying samples for analysis and calculating the desired information from the intensity traces. Analyzing giant unilamellar vesicles (GUVs) is one ...

Denoising of pediatric low dose abdominal CT using deep learning based algorithm.

PloS one
OBJECTIVES: To evaluate standard dose-like computed tomography (CT) images generated by a deep learning method, trained using unpaired low-dose CT (LDCT) and standard-dose CT (SDCT) images.

Fast Panoptic Segmentation with Soft Attention Embeddings.

Sensors (Basel, Switzerland)
Panoptic segmentation provides a rich 2D environment representation by unifying semantic and instance segmentation. Most current state-of-the-art panoptic segmentation methods are built upon two-stage detectors and are not suitable for real-time appl...