AIMC Topic: Image Processing, Computer-Assisted

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A Holistically-Nested U-Net: Surgical Instrument Segmentation Based on Convolutional Neural Network.

Journal of digital imaging
Surgical instrument segmentation is an essential task in the domain of computer-assisted surgical system. It is critical to increase the context-awareness of surgeons during the operation. We propose a new model based on the U-Net architecture for su...

Semi-automated prediction approach of target shifts using machine learning with anatomical features between planning and pretreatment CT images in prostate radiotherapy.

Journal of radiation research
The goal of this study was to develop a semi-automated prediction approach of target shifts using machine learning architecture (MLA) with anatomical features for prostate radiotherapy. Our hypothesis was that anatomical features between planning com...

A reference library for assigning protein subcellular localizations by image-based machine learning.

The Journal of cell biology
Confocal micrographs of EGFP fusion proteins localized at key cell organelles in murine and human cells were acquired for use as subcellular localization landmarks. For each of the respective 789,011 and 523,319 optically validated cell images, morph...

Computer-assisted Diagnosis of Breast Cancer by Cell Network Matrix Extraction and Multilayer Perceptron Analysis.

Annals of clinical and laboratory science
OBJECTIVE: Diagnosis of breast cancer is based on identification of various morphologic features by histopathologic examination of the specimen. Ancillary immunohistochemical and molecular analyses provide additional information that is prognostic an...

Application of Convolutional Neural Networks for Detection of Superficial Nonampullary Duodenal Epithelial Tumors in Esophagogastroduodenoscopic Images.

Clinical and translational gastroenterology
OBJECTIVES: A superficial nonampullary duodenal epithelial tumor (SNADET) is defined as a mucosal or submucosal sporadic tumor of the duodenum that does not arise from the papilla of Vater. SNADETs rarely metastasize to the lymph nodes, and most can ...

MLCD: A Unified Software Package for Cancer Diagnosis.

JCO clinical cancer informatics
PURPOSE: Machine Learning Package for Cancer Diagnosis (MLCD) is the result of a National Institutes of Health/National Cancer Institute (NIH/NCI)-sponsored project for developing a unified software package from state-of-the-art breast cancer biopsy ...

Research Techniques Made Simple: Deep Learning for the Classification of Dermatological Images.

The Journal of investigative dermatology
Deep learning is a branch of artificial intelligence that uses computational networks inspired by the human brain to extract patterns from raw data. Development and application of deep learning methods for image analysis, including classification, se...

Machine Learning for Analysis of Microscopy Images: A Practical Guide.

Current protocols in cell biology
The explosive growth of machine learning has provided scientists with insights into data in ways unattainable using prior research techniques. It has allowed the detection of biological features that were previously unrecognized and overlooked. Howev...

[Research and application of orthotopic DR chest radiograph quality control system based on artificial intelligence].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
With the change of medical diagnosis and treatment mode, the quality of medical image directly affects the diagnosis and treatment of the disease for doctors. Therefore, realization of intelligent image quality control by computer will have a greater...