AIMC Topic: Image Processing, Computer-Assisted

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Large-Scale Multi-Class Image-Based Cell Classification With Deep Learning.

IEEE journal of biomedical and health informatics
Recent advances in ultra-high-throughput microscopy have enabled a new generation of cell classification methodologies using image-based cell phenotypes alone. In contrast to current single-cell analysis techniques that rely solely on slow and costly...

Intra-Slice Motion Correction of Intravascular OCT Images Using Deep Features.

IEEE journal of biomedical and health informatics
Intra-slice motion correction is an important step for analyzing volume variations and pathological formations from intravascular imaging. Optical coherence tomography (OCT) has been recently introduced for intravascular imaging and assessment of cor...

Learning deep similarity metric for 3D MR-TRUS image registration.

International journal of computer assisted radiology and surgery
PURPOSE: The fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images for guiding targeted prostate biopsy has significantly improved the biopsy yield of aggressive cancers. A key component of MR-TRUS fusion is image registration. H...

Diabetic Retinopathy Diagnosis from Retinal Images Using Modified Hopfield Neural Network.

Journal of medical systems
Disease diagnosis from medical images has become increasingly important in medical science. Abnormality identification in retinal images has become a challenging task in medical science. Effective machine learning and soft computing methods should be...

A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition.

PloS one
The surface electromyography (sEMG)-based gesture recognition with deep learning approach plays an increasingly important role in human-computer interaction. Existing deep learning architectures are mainly based on Convolutional Neural Network (CNN) ...

Translation of morphological and functional musculoskeletal imaging.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
In an effort to develop quantitative biomarkers for degenerative joint disease and fill the void that exists for diagnosing, monitoring, and assessing the extent of whole joint degeneration, the past decade has been marked by a greatly increased role...

A novel MRI segmentation method using CNN-based correction network for MRI-guided adaptive radiotherapy.

Medical physics
PURPOSE: The purpose of this study was to expedite the contouring process for MRI-guided adaptive radiotherapy (MR-IGART), a convolutional neural network (CNN) deep-learning (DL) model is proposed to accurately segment the liver, kidneys, stomach, bo...

Individualized prediction of dispositional worry using white matter connectivity.

Psychological medicine
BACKGROUND: Excessive worry is a defining feature of generalized anxiety disorder and is present in a wide range of other psychiatric conditions. Therefore, individualized predictions of worry propensity could be highly relevant in clinical practice,...

RSDNet: Learning to Predict Remaining Surgery Duration from Laparoscopic Videos Without Manual Annotations.

IEEE transactions on medical imaging
Accurate surgery duration estimation is necessary for optimal OR planning, which plays an important role in patient comfort and safety as well as resource optimization. It is, however, challenging to preoperatively predict surgery duration since it v...

Acquisition and reconstruction of 4D surfaces of axolotl embryos with the flipping stage robotic microscope.

Bio Systems
We have designed and constructed a Flipping Stage for a light microscope that can view the whole exterior surface of a 2 mm diameter developing axolotl salamander embryo. It works by rapidly inverting the bottom-heavy embryo, imaging it as it rights ...