AIMC Topic: Microscopy
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Healthy and unhealthy red blood cell detection in human blood smears using neural networks.
Micron (Oxford, England : 1993)
Feb 1, 2016
One of the most common diseases that affect human red blood cells (RBCs) is anaemia. To diagnose anaemia, the following methods are typically employed: an identification process that is based on measuring the level of haemoglobin and the classificati...
Deep Voting: A Robust Approach Toward Nucleus Localization in Microscopy Images.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Nov 18, 2015
Robust and accurate nuclei localization in microscopy image can provide crucial clues for accurate computer-aid diagnosis. In this paper, we propose a convolutional neural network (CNN) based hough voting method to localize nucleus centroids with hea...
Interactive Cell Segmentation Based on Active and Semi-Supervised Learning.
IEEE transactions on medical imaging
Oct 26, 2015
Automatic cell segmentation can hardly be flawless due to the complexity of image data particularly when time-lapse experiments last for a long time without biomarkers. To address this issue, we propose an interactive cell segmentation method by clas...
An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images.
Scientific reports
Oct 9, 2015
This research proposes an intelligent decision support system for acute lymphoblastic leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with stimulating discriminant measures (SDM) of both within- and between-cluster sca...
Automatic Identification of Human Erythrocytes in Microscopic Fecal Specimens.
Journal of medical systems
Sep 9, 2015
Traditional fecal erythrocyte detection is performed via a manual operation that is unsuitable because it depends significantly on the expertise of individual inspectors. To recognize human erythrocytes automatically and precisely, automatic segmenta...
Feasibility of transoral robotic-assisted high-resolution microendoscopic imaging of oropharyngeal squamous cell carcinoma.
Head & neck
Jun 18, 2015
BACKGROUND: Transoral robotic-assisted oncologic surgery of the head and neck offers promising functional results. Nonetheless, the efficacy of oncologic surgery remains critically dependent on obtaining negative margins. We aimed to integrate a mini...
Novel structural descriptors for automated colon cancer detection and grading.
Computer methods and programs in biomedicine
Jun 6, 2015
The histopathological examination of tissue specimens is necessary for the diagnosis and grading of colon cancer. However, the process is subjective and leads to significant inter/intra observer variation in diagnosis as it mainly relies on the visua...
Force adaptive robotically assisted endomicroscopy for intraoperative tumour identification.
International journal of computer assisted radiology and surgery
Apr 23, 2015
PURPOSE: For effective tumour margin definition for cancer surgery, there is an increasing demand for the development of real-time intraoperative tissue biopsy techniques. Recent advances in miniaturized biophotonics probes have permitted the develop...
Computer-aided diagnosis from weak supervision: a benchmarking study.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 20, 2014
Supervised machine learning is a powerful tool frequently used in computer-aided diagnosis (CAD) applications. The bottleneck of this technique is its demand for fine grained expert annotations, which are tedious for medical image analysis applicatio...
Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 12, 2014
Shape based active contours have emerged as a natural solution to overlap resolution. However, most of these shape-based methods are computationally expensive. There are instances in an image where no overlapping objects are present and applying thes...
Image Interpretation, Computer-Assisted
Pattern Recognition, Automated
Image Enhancement
Oligonucleotide Array Sequence Analysis
Humans
Subtraction Technique
Algorithms
Machine Learning
Prostatic Neoplasms
Cell Nucleus Shape
Reproducibility of Results
Neoplasm Grading
Sensitivity and Specificity
Microscopy
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