Deformable models in medical image analysis: a survey
This article surveys deformable models, a promising and vigorously researched computer-
assisted medical image analysis technique. Among model-based techniques, deformable …
assisted medical image analysis technique. Among model-based techniques, deformable …
Edge and line oriented contour detection: State of the art
We present an overview of various edge and line oriented approaches to contour detection
that have been proposed in the last two decades. By edge and line oriented we mean …
that have been proposed in the last two decades. By edge and line oriented we mean …
Convolutional neural networks for medical image analysis: Full training or fine tuning?
Training a deep convolutional neural network (CNN) from scratch is difficult because it
requires a large amount of labeled training data and a great deal of expertise to ensure …
requires a large amount of labeled training data and a great deal of expertise to ensure …
Convolutional networks can learn to generate affinity graphs for image segmentation
Many image segmentation algorithms first generate an affinity graph and then partition it. We
present a machine learning approach to computing an affinity graph using a convolutional …
present a machine learning approach to computing an affinity graph using a convolutional …
PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques
Historically, anatomical CT and MR images were used to delineate the gross tumour
volumes (GTVs) for radiotherapy treatment planning. The capabilities offered by modern …
volumes (GTVs) for radiotherapy treatment planning. The capabilities offered by modern …
Discovering mammography-based machine learning classifiers for breast cancer diagnosis
This work explores the design of mammography-based machine learning classifiers (MLC)
and proposes a new method to build MLC for breast cancer diagnosis. We massively …
and proposes a new method to build MLC for breast cancer diagnosis. We massively …
[PDF][PDF] A review of medical image segmentation: methods and available software
Automatic medical image segmentation is an unsolved problem that has captured the
attention of many researchers. The purpose of this survey is to identify a representative set of …
attention of many researchers. The purpose of this survey is to identify a representative set of …
Automating carotid intima-media thickness video interpretation with convolutional neural networks
Cardiovascular disease (CVD) is the leading cause of mortality yet largely preventable, but
the key to prevention is to identify at risk individuals before adverse events. For predicting …
the key to prevention is to identify at risk individuals before adverse events. For predicting …
Oriented active shape models
Active shape models (ASM) are widely employed for recognizing anatomic structures and for
delineating them in medical images. In this paper, a novel strategy called oriented active …
delineating them in medical images. In this paper, a novel strategy called oriented active …