AIMC Topic: Deep Learning

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Cell Counting and Segmentation of Immunohistochemical Images in the Spinal Cord: Comparing Deep Learning and Traditional Approaches.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Estimation of cell nuclei in images stained for the c-fos protein using immunohistochemistry (IHC) is infeasible in large image sets. Use of multiple human raters to increase throughput often creates variance in the data analysis. Machine learning te...
Spinal Cord Humans Deep Learning Immunohistochemistry
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Automated Classification Using End-to-End Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
According to a study [1] by the Ministry of Health in Singapore, since 2009, cancer, ischaemic heart disease and pneumonia together accounted for approximately 60% of the total causes of death. It has been 9 years, and Pneumonia and other Acute Upper...
Singapore Neural Networks, Computer Diagnosis, Computer-Assisted Quality of Life Deep Learning
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A New and Improved Method for Automated Screening of Age-Related Macular Degeneration Using Ensemble Deep Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
In this paper, we provide a new framework on deep learning based automated screening method for finding individuals at risk of developing Age-related Macular Degeneration (AMD). We studied the appropriateness of using the transfer learning to screen ...
Neural Networks, Computer Image Interpretation, Computer-Assisted Deep Learning Humans Fundus Oculi Macular Degeneration
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Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Bone age is an essential measure of skeletal maturity in children with growth disorders. It is typically assessed by a trained physician using radiographs of the hand and a reference model. However, it has been described that the reference models lea...
Deep Learning Adolescent Hand Bones Humans Child Young Adult Normal Distribution Retrospective Studies Radiography Infant Age Determination by Skeleton Female Child, Preschool Image Interpretation, Computer-Assisted Observer Variation Infant, Newborn
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Fusing Results of Several Deep Learning Architectures for Automatic Classification of Normal and Diabetic Macular Edema in Optical Coherence Tomography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Diabetic Macular Edema (DME) is a severe eye disease that can lead to irreversible blindness if it is left untreated. DME diagnosis still relies on manual evaluation from opthalmologists, thus the process is time consuming and diagnosis may be subjec...
Macular Edema Diabetes Complications Principal Component Analysis Tomography, Optical Coherence Humans Algorithms Deep Learning Neural Networks, Computer
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Fully Convolutional DenseNets for Segmentation of Microvessels in Two-photon Microscopy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Segmentation of microvessels measured using two-photon microscopy has been studied in the literature with limited success due to uneven intensities associated with optical imaging and shadowing effects. In this work, we address this problem using a c...
Photons Microvessels Humans Neural Networks, Computer Image Processing, Computer-Assisted Microscopy Deep Learning
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Patch-level Tumor Classification in Digital Histopathology Images with Domain Adapted Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Tumor histopathology is a crucial step in cancer diagnosis which involves visual inspection of imaging data to detect the presence of tumor cells among healthy tissues. This manual process can be time-consuming, error-prone, and influenced by the exp...
Humans Neural Networks, Computer ROC Curve Area Under Curve Image Interpretation, Computer-Assisted Neoplasms Deep Learning Histological Techniques
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Colorization of H&E stained tissue using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Histopathology is a critical tool in the diagnosis and stratification of cancer. Digital Pathology involves the scanning of stained and fixed tissue samples to produce highresolution images that can be used for computer-aided diagnosis and research. ...
Deep Learning Neoplasms Humans Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Staining and Labeling Color
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Deep Learning Models Differentiate Tumor Grades from H&E Stained Histology Sections.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Aberration in tissue architecture is an essential index for cancer diagnosis and tumor grading. Therefore, extracting features of aberrant phenotypes and classification of the histology tissue can provide a model for computer-aided pathology (CAP). A...
Neoplasm Grading Histological Techniques Neural Networks, Computer Deep Learning Humans
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CardioXNet: Automated Detection for Cardiomegaly Based on Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
In this paper, we present an automated procedure to determine the presence of cardiomegaly on chest X-ray image based on deep learning. The proposed algorithm CardioXNet uses deep learning methods U-NET and cardiothoracic ratio for diagnosis of cardi...
Algorithms Deep Learning Cardiomegaly Humans Neural Networks, Computer
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