AIMC Topic: Algorithms

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Pixel-to-Pixel Learning With Weak Supervision for Single-Stage Nucleus Recognition in Ki67 Images.

IEEE transactions on bio-medical engineering
OBJECTIVE: Nucleus recognition is a critical yet challenging step in histopathology image analysis, for example, in Ki67 immunohistochemistry stained images. Although many automated methods have been proposed, most use a multi-stage processing pipeli...

Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography.

IEEE transactions on medical imaging
Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to establish a diagnosis. Over the past decades, the automation of this task has been the subject of intense research. In this paper, we evaluate how far...

Active learning using rough fuzzy classifier for cancer prediction from microarray gene expression data.

Journal of biomedical informatics
Cancer classification from microarray gene expression data is one of the important areas of research in the field of computational biology and bioinformatics. Traditional supervised techniques often fail to produce desired accuracy as the number of c...

Deep Learning-Based Framework for Identification of Glioblastoma Tumor using Hyperspectral Images of Human Brain.

Sensors (Basel, Switzerland)
The main goal of brain cancer surgery is to perform an accurate resection of the tumor, preserving as much normal brain tissue as possible for the patient. The development of a non-contact and label-free method to provide reliable support for tumor r...

A novel framework of multivariate modeling of water distribution network through 3 factorial design and artificial neural network.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
The water distribution network is largely affected by the change in the influencing factors, such as input pressure, demand and supply duration. The change in each parameter requires the extensive design of the network and the interactive effect of t...

Implementing artificial neural networks through bionic construction.

PloS one
It is evident through biology research that, biological neural network could be implemented through two means: by congenital heredity, or by posteriority learning. However, traditionally, artificial neural network, especially the Deep learning Neural...

Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying.

Surgical endoscopy
INTRODUCTION: The most common way of assessing surgical performance is by expert raters to view a surgical task and rate a trainee's performance. However, there is huge potential for automated skill assessment and workflow analysis using modern techn...

3D convolutional neural networks for tumor segmentation using long-range 2D context.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
We present an efficient deep learning approach for the challenging task of tumor segmentation in multisequence MR images. In recent years, Convolutional Neural Networks (CNN) have achieved state-of-the-art performances in a large variety of recogniti...

The Adaptive Hermite Fractal Tree (AHFT): a novel surgical 3D path planning approach with curvature and heading constraints.

International journal of computer assisted radiology and surgery
PURPOSE: In the context of minimally invasive neurosurgery, steerable needles such as the one developed within the Horizon2020-funded EDEN2020 project (Frasson et al. in Proc Inst Mech Eng Part H J Eng Med 224(6):775-88, 2010. https://doi.org/10.1243...

Fast Subgraph Matching Strategies Based on Pattern-Only Heuristics.

Interdisciplinary sciences, computational life sciences
Many scientific applications entail solving the subgraph isomorphism problem, i.e., given an input pattern graph, find all the subgraphs of a (usually much larger) target graph that are structurally equivalent to that input. Because subgraph isomorph...