AIMC Journal:
Medical image analysis

Showing 561 to 570 of 699 articles

Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis.

Medical image analysis Mar 29, 2019
Machine learning (ML) algorithms have made a tremendous impact in the field of medical imaging. While medical imaging datasets have been growing in size, a challenge for supervised ML algorithms that is frequently mentioned is the lack of annotated d...
Humans Image Processing, Computer-Assisted Supervised Machine Learning Diagnostic Imaging
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Pulmonary nodule detection in CT scans with equivariant CNNs.

Medical image analysis Mar 28, 2019
Convolutional Neural Networks (CNNs) require a large amount of annotated data to learn from, which is often difficult to obtain for medical imaging problems. In this work we show that the sample complexity of CNNs can be significantly improved by usi...
Neural Networks, Computer Tomography, X-Ray Computed Humans Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Deep Learning Imaging, Three-Dimensional
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Integrating spatial configuration into heatmap regression based CNNs for landmark localization.

Medical image analysis Mar 25, 2019
In many medical image analysis applications, only a limited amount of training data is available due to the costs of image acquisition and the large manual annotation effort required from experts. Training recent state-of-the-art machine learning met...
Magnetic Resonance Imaging Anatomic Landmarks Cephalometry Imaging, Three-Dimensional Image Processing, Computer-Assisted Spine Hand Neural Networks, Computer Tomography, X-Ray Computed Humans
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Patient-attentive sequential strategy for perimetry-based visual field acquisition.

Medical image analysis Mar 23, 2019
Perimetry is a non-invasive clinical psychometric examination used for diagnosing ophthalmic and neurological conditions. At its core, perimetry relies on a subject pressing a button whenever they see a visual stimulus within their field of view. Thi...
Monte Carlo Method Glaucoma Algorithms Visual Fields Visual Field Tests Psychometrics Humans Neural Networks, Computer
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A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning.

Medical image analysis Mar 22, 2019
In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method combines a contrast-adaptive generative model for whole-brain segmentation...
Organs at Risk Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Magnetic Resonance Imaging Glioblastoma Neural Networks, Computer Brain Neoplasms Humans
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BIRNet: Brain image registration using dual-supervised fully convolutional networks.

Medical image analysis Mar 22, 2019
In this paper, we propose a deep learning approach for image registration by predicting deformation from image appearance. Since obtaining ground-truth deformation fields for training can be challenging, we design a fully convolutional network that i...
Humans Neural Networks, Computer Deep Learning Brain Mapping Image Processing, Computer-Assisted Magnetic Resonance Imaging
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CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.

Medical image analysis Mar 21, 2019
Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is a crucial step for radiation therapy in the treatment of prostate cancer. However, it is a very challenging task due to unclear boundaries, large intr...
Tomography, X-Ray Computed Male Deep Learning Humans Radiographic Image Interpretation, Computer-Assisted Organs at Risk Urinary Bladder Prostatic Neoplasms Rectum Imaging, Three-Dimensional
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Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

Medical image analysis Feb 27, 2019
Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is a highly subjective and labor-intensive task. Previous efforts to automate tumor prolifera...
Mitosis Pathology Deep Learning Image Processing, Computer-Assisted Predictive Value of Tests Gene Expression Cell Proliferation Female Breast Neoplasms Biomarkers, Tumor Humans Prognosis
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Deep-learning based multiclass retinal fluid segmentation and detection in optical coherence tomography images using a fully convolutional neural network.

Medical image analysis Feb 22, 2019
As a non-invasive imaging modality, optical coherence tomography (OCT) can provide micrometer-resolution 3D images of retinal structures. These images can help reveal disease-related alterations below the surface of the retina, such as the presence o...
Humans Deep Learning Imaging, Three-Dimensional Retina Image Processing, Computer-Assisted Tomography, Optical Coherence
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Medical image classification using synergic deep learning.

Medical image analysis Feb 18, 2019
The classification of medical images is an essential task in computer-aided diagnosis, medical image retrieval and mining. Although deep learning has shown proven advantages over traditional methods that rely on the handcrafted features, it remains c...
Information Storage and Retrieval Radiology Information Systems Image Processing, Computer-Assisted Diagnostic Imaging Data Mining Diagnosis, Computer-Assisted Deep Learning Humans Neural Networks, Computer
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