AIMC Topic: Image Processing, Computer-Assisted

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Deep learning-based whole-heart segmentation in 4D contrast-enhanced cardiac CT.

Computers in biology and medicine
Automatic cardiac chamber and left ventricular (LV) myocardium segmentation over the cardiac cycle significantly extends the utilization of contrast-enhanced cardiac CT, potentially enabling in-depth assessment of cardiac function. Therefore, we eval...

Tiled Sparse Coding in Eigenspaces for Image Classification.

International journal of neural systems
The automation in the diagnosis of medical images is currently a challenging task. The use of Computer Aided Diagnosis (CAD) systems can be a powerful tool for clinicians, especially in situations when hospitals are overflowed. These tools are usuall...

Digital Technology in Diagnostic Breast Pathology and Immunohistochemistry.

Pathobiology : journal of immunopathology, molecular and cellular biology
Digital technology has been used in the field of diagnostic breast pathology and immunohistochemistry (IHC) for decades. Examples include automated tissue processing and staining, digital data processing, storing and management, voice recognition sys...

Model-Driven Deep Learning Method for Pancreatic Cancer Segmentation Based on Spiral-Transformation.

IEEE transactions on medical imaging
Pancreatic cancer is a lethal malignant tumor with one of the worst prognoses. Accurate segmentation of pancreatic cancer is vital in clinical diagnosis and treatment. Due to the unclear boundary and small size of cancers, it is challenging to both m...

On the Performance of Generative Adversarial Network by Limiting Mode Collapse for Malware Detection Systems.

Sensors (Basel, Switzerland)
Generative adversarial network (GAN) has been regarded as a promising solution to many machine learning problems, and it comprises of a generator and discriminator, determining patterns and anomalies in the input data. However, GANs have several comm...

Automatic Pancreatic Cyst Lesion Segmentation on EUS Images Using a Deep-Learning Approach.

Sensors (Basel, Switzerland)
The automatic segmentation of the pancreatic cyst lesion (PCL) is essential for the automated diagnosis of pancreatic cyst lesions on endoscopic ultrasonography (EUS) images. In this study, we proposed a deep-learning approach for PCL segmentation on...

Unsupervised discovery of dynamic cell phenotypic states from transmitted light movies.

PLoS computational biology
Identification of cell phenotypic states within heterogeneous populations, along with elucidation of their switching dynamics, is a central challenge in modern biology. Conventional single-cell analysis methods typically provide only indirect, static...

SAFRON: Stitching Across the Frontier Network for Generating Colorectal Cancer Histology Images.

Medical image analysis
Automated synthesis of histology images has several potential applications including the development of data-efficient deep learning algorithms. In the field of computational pathology, where histology images are large in size and visual context is c...

Extracting Rectified Building Footprints from Traditional Orthophotos: A New Workflow.

Sensors (Basel, Switzerland)
Deep learning techniques such as convolutional neural networks have largely improved the performance of building segmentation from remote sensing images. However, the images for building segmentation are often in the form of traditional orthophotos, ...

Generative Adversarial Networks for Morphological-Temporal Classification of Stem Cell Images.

Sensors (Basel, Switzerland)
Frequently, neural network training involving biological images suffers from a lack of data, resulting in inefficient network learning. This issue stems from limitations in terms of time, resources, and difficulty in cellular experimentation and data...