AIMC Topic: Image Processing, Computer-Assisted

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Data Representations for Segmentation of Vascular Structures Using Convolutional Neural Networks with U-Net Architecture.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Convolutional neural networks (CNNs) produce promising results when applied to a wide range of medical imaging tasks including the segmentation of tissue structures. However, segmentation is particularly challenging when the target structures are sma...

Boundary-aware Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Breast ultrasound (US) is an effective imaging modality for breast cancer diagnosis. US computer-aided diagnosis (CAD) systems have been developed for decades and have employed either conventional handcrafted features or modern automatic deep-learned...

Retinal Vessel Segmentation using Round-wise Features Aggregation on Bracket-shaped Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
With the recent advent of deep learning in medical image processing, retinal blood vessel segmentation topic has been comprehensively handled by numerous research works. However, since the ratio between the number of vessel and background pixels is h...

Advances in Auto-Segmentation.

Seminars in radiation oncology
Manual image segmentation is a time-consuming task routinely performed in radiotherapy to identify each patient's targets and anatomical structures. The efficacy and safety of the radiotherapy plan requires accurate segmentations as these regions of ...

An End-to-end System for Automatic Characterization of Iba1 Immunopositive Microglia in Whole Slide Imaging.

Neuroinformatics
Traumatic brain injury (TBI) is one of the leading causes of death and disability worldwide. Detailed studies of the microglial response after TBI require high throughput quantification of changes in microglial count and morphology in histological se...

May I Keep an Eye on Your Training? Gait Assessment Assisted by a Mobile Robot.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
A successful rehabilitation after surgery in hip endoprosthetics comprises self-training of the lessons taught by physiotherapists. While doing this, immediate feedback to the patient about deviations from physiological gait patterns during training ...

Transfer learning based deep CNN for segmentation and detection of mitoses in breast cancer histopathological images.

Microscopy (Oxford, England)
Segmentation and detection of mitotic nuclei is a challenging task. To address this problem, a Transfer Learning based fast and accurate system is proposed. To give the classifier a balanced dataset, this work exploits the concept of Transfer Learnin...

A Platform Integrating Acquisition, Reconstruction, Visualization, and Manipulator Control Modules for MRI-Guided Interventions.

Journal of digital imaging
This work presents a platform that integrates a customized MRI data acquisition scheme with reconstruction and three-dimensional (3D) visualization modules along with a module for controlling an MRI-compatible robotic device to facilitate the perform...

Automatic Lumbar MRI Detection and Identification Based on Deep Learning.

Journal of digital imaging
The aim of this research is to automatically detect lumbar vertebras in MRI images with bounding boxes and their classes, which can assist clinicians with diagnoses based on large amounts of MRI slices. Vertebras are highly semblable in appearance, l...