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BMAI

Biomedical Artificial
Intelligence Research Unit

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Computerized Detection of Lung Nodules in Low-Dose CT, Part I: Basic Principle of Massive-Training Artificial Neural Network (MTANN) for Reduction of False Positives

Computerized Detection of Lung Nodules in Low-Dose CT, Part I: Basic Principle of Massive-Training Artificial Neural Network (MTANN) for Reduction of False Positives

We investigated a novel pattern-recognition technique based on an artificial neural network (ANN), called a massive-training artificial neural network (MTANN), for reduction of false positives (FPs) in computerized detection of lung nodules in low-dose CT. The MTANN consists of a linear-output multilayer ANN model, which is capable of operating on image data directly. The MTANN is trained by us Read more...

Research Area :
DML
Clinical Area :
BI
Anatomy :
Chest
Automated CT Liver Volumetry by Use of Three-Dimensional Fast-Marching and Level-Set Segmentation

Automated CT Liver Volumetry by Use of Three-Dimensional Fast-Marching and Level-Set Segmentation

We developed an automated scheme for segmenting and calculating liver volume in hepatic CT by means of 3D fast-marching and level-set segmentation algorithms. Automatic liver segmentation on hepatic CT images is challenging because the liver often abuts other organs of similar density. Our purpose was to develop an automated liver segmentation scheme based on a 3D level-set algorithm for measur Read more...

Research Area :
AIAD
Clinical Area :
BI
Anatomy :
Abdomen
Enhanced Digital Chest Radiography: Temporal Subtraction Combined with Virtual Dual-EnergyETechnology for Improved Conspicuity of Growing Cancers and Other Pathologic Changes

Enhanced Digital Chest Radiography: Temporal Subtraction Combined with Virtual Dual-EnergyETechnology for Improved Conspicuity of Growing Cancers and Other Pathologic Changes

Enhanced Digital Chest Radiography: Temporal Subtraction Combined with Virtual Dual-EnergyETechnology for Improved Conspicuity of Growing Cancers and Other Pathologic Changes

We developed a novel temporal-subtraction (TS) technique combined with virtual dual-energyEtechnology for improved conspicuity of growing cancers and other pathologic changes in digital chest radiography (CXR). Digi Read more...

Research Area :
AII
Clinical Area :
BI
Anatomy :
Chest