Track topics on Twitter Track topics that are important to you
We propose Neural Image Compression (NIC), a two-step method to build convolutional neural networks for gigapixel image analysis solely using weak image-level labels. First, gigapixel images are compressed using a neural network trained in an unsupervised fashion, retaining high-level information while suppressing pixel-level noise. Second, a convolutional neural network (CNN) is trained on these compressed image representations to predict image-level labels, avoiding the need for fine-grained manual annotations. We compared several encoding strategies, namely reconstruction error minimization, contrastive training and adversarial feature learning, and evaluated NIC on a synthetic task and two public histopathology datasets. We found that NIC can exploit visual cues associated with image-level labels successfully, integrating both global and local visual information. Furthermore, we visualized the regions of the input gigapixel images where the CNN attended to, and confirmed that they overlapped with annotations from human experts.
This article was published in the following journal.
Name: IEEE transactions on pattern analysis and machine intelligence
Enabling automated pipelines, image analysis and big data methodology in cancer clinics requires thorough understanding of the data. Automated quality assurance steps could improve the efficiency and ...
Although convolutional neural networks have achieved tremendous success on histopathology image classification, they usually require large-scale clean annotated data and are sensitive to noisy labels....
We describe Orbit Image Analysis, an open-source whole slide image analysis tool. The tool consists of a generic tile-processing engine which allows the execution of various image analysis algorithms ...
Deep learning models and specifically Convolutional Neural Networks (CNNs) are becoming the leading approach in many computer vision tasks, including medical image analysis. Nevertheless, the CNN trai...
Image style transfer is to re-render the content of one image with the style of another. Most existing methods couple content and style information in their network structures and hyper-parameters, an...
Patient-assisted compression (PAC) allows the patient to participate in controlling the amount of compression force during mammography and is a personalized approach that has demonstrated ...
To validate the following theory: "With TRUVIEW ART™ applied a detector's quantitative performance index, MTF(Modulation Transfer Function), is increased 20% or more". This is to examine...
To evaluate the difference between body image and self-esteem scores during and at the end of the medical. Hypothesis: body image and self-esteem changes during the oncological treatments.
The purpose of this research study is to develop CT scanning and image analysis techniques to help define and measure several key properties of the pulmonary system that cannot be obtained...
Patients with lymphedema may experience pain and body image issues. This study investigates the effect of Combined Decongestive Therapy and pneumatic compression pump on body image in pati...
A technique encompassing morphometry, densitometry, neural networks, and expert systems that has numerous clinical and research applications and is particularly useful in anatomic pathology for the study of malignant lesions. The most common current application of image cytometry is for DNA analysis, followed by quantitation of immunohistochemical staining.
A method of delineating blood vessels by subtracting a tissue background image from an image of tissue plus intravascular contrast material that attenuates the X-ray photons. The background image is determined from a digitized image taken a few moments before injection of the contrast material. The resulting angiogram is a high-contrast image of the vessel. This subtraction technique allows extraction of a high-intensity signal from the superimposed background information. The image is thus the result of the differential absorption of X-rays by different tissues.
The production of an image obtained by cameras that detect the radioactive emissions of an injected radionuclide as it has distributed differentially throughout tissues in the body. The image obtained from a moving detector is called a scan, while the image obtained from a stationary camera device is called a scintiphotograph.
A visual image which is recalled in accurate detail. It is a sort of projection of an image on a mental screen.
X-ray image-detecting devices that make a focused image of body structures lying in a predetermined plane from which more complex images are computed.