Saturday, 29 June 2013
Lobaton Devises X-ray Approach to Track Surgical Devices and Minimize Radiation Exposure
Dr. Edgar Lobaton
Dr. Edgar Lobaton, Assistant Professor of Electrical and Computer Engineering at NC State University, and Researches from The University of North Carolina at Chapel Hill (UNC) have developed a new tool to help surgeons use X-rays to track devices used in "minimally invasive" surgical procedures while also limiting the patient's exposure to radiation from the X-rays.
Many surgical procedures now use long, thin devices - such as "steerable needles" - that can be inserted into a patient's body through a small incision and then steered to a target location. These "minimally invasive" procedures allow doctors to perform surgeries without having to make major incisions, which decreases the risk of infection and shortens the patient's recovery time.
However, these techniques pose a challenge to surgeons, because it is difficult for them to determine precisely where the surgical device is in the patient's body.
One solution to the problem is to use X-rays to track the progress of the surgical device in the patient. But doctors want to minimize the number of X-rays taken, in order to limit the patient's exposure to radiation.
"We have now developed an algorithm to determine the fewest number of X-rays that need to be taken, as well as what angles they need to be taken from, in order to give surgeons the information they need on a surgical device's location in the body," says Dr. Lobaton, lead author of a paper on the research.
This graphic illustrates a surgical tool in a human lung. The blue curve corresponds to what we expect the device to do. The green curve represents what would happen in a real procedure were some perturbations introduced. The red-dots represent the estimated shape based on where the new x-ray algorithm says the surgical tool actually is. (Click to enlarge. Image credit: Edgar Lobaton.)
The new tool is a computer program that allows surgeons to enter what type of procedure they'll be performing and how precise they need the location data to be. Those variables are then plugged into the algorithm developed by the research team, which tells the surgeon how many X-rays will be needed - and from which angles - to produce the necessary location details.
For example, if a surgeon needs only a fairly general idea of where a device is located, only two or three X-rays may be needed - whereas more X-rays would be required if the surgeon needs extremely precise location data.
The paper, "Continuous Shape Estimation of Continuum Robots Using X-ray Images," will be presented at the IEEE International Conference on Robotics and Automation, being held in Karlsruhe, Germany, May 6-10. The paper was co-authored by Jingua Fu, a former graduate student at UNC; Luis Torres, a Ph.D. student at UNC; and Dr. Ron Alterovitz, an assistant professor of computer science at UNC. The research was supported by the National Science Foundation and the National Institutes of Health.
You can read the paper that was will be presented on May 6-10, 2013 at the IEEE International Conference on Robotics and Automation in Karlsruhe, Germany, below.
"Continuous Shape Estimation of Continuum Robots Using X-ray Images"
Authors: Edgar J. Lobaton, North Carolina State University; Jingua Fu, Luis G. Torres and Ron Alterovitz, University of North Carolina at Chapel Hill
Presented: May 6-10, 2013, IEEE International Conference on Robotics and Automation, Karlsruhe, Germany
Abstract: We present a new method for estimating the shape of a continuum robot continuously during a medical procedure using a small number of X-ray projection images. Continuum robots have curvilinear structure, enabling them to maneuver through constrained spaces in a snake-like manner. An accurate estimate of the robot's shape is crucial for the success of procedures that require avoidance of anatomical obstacles and sensitive tissues. Online shape estimation of a continuum robot is complicated by uncertainty in its kinematic model, movement of the robot during the procedure, noise in X-ray images, and the clinical need to minimize the number of X-ray images acquired. Our new method integrates kinematics models of the robot with data extracted from an optimally selected set of X-ray projection images. Our method represents the shape of the continuum robot over time as a deformable surface which can be described as a linear combination of time and space bases. We take advantage of probabilistic priors and numeric optimization to select optimal camera configurations, thus minimizing the expected shape estimation error. We evaluate our method using simulated concentric tube robot procedures and demonstrate that obtaining 3 images from viewpoints selected by our method achieves shape estimation errors significantly lower than using the kinematic model alone or using uniformly spaced viewpoints.
Tuesday, 18 June 2013
In the Google age, approach to education needs a rethink
Would a person with good handwriting, spelling and grammar and instant recall of multiplication tables be considered a better candidate for a job than, say, one who knows how to configure a peer-to-peer network of devices, set up an organisation-wide Google calendar and find out where the most reliable sources of venture capital are, I wonder? The former set of skills is taught in schools, the latter is not.
In school examinations, learners must reproduce facts from memory, solve problems using their minds and paper alone. They must not talk to anyone or look at anyone else’s work. They must not use any educational resources, certainly not the Internet.
When they complete their schooling and start a job, they are told to solve problems in groups, through meetings, using every resource they can think of. They are rewarded for solving problems this way — for not using the methods they were taught in school.
The curriculum lists things that children must learn. There is no list stating why these things are important. A child being taught the history of Vikings in England says to me: “We could have found out all that in five minutes if we ever needed to.”
One of the teachers who works with me said to her class of nine-year-olds: “There is something called electromagnetic radiation that we can’t see, can you figure out what it is?”
The children huddle around a few computers, talking, running around and looking for clues. In about 40 minutes, they figure out the basics of electromagnetism and start relating it to mobile signals.
One of them says: “Aren’t we going to do any work?”
“What do you think you were doing?” asks the teacher.
If examinations challenge learners to solve problems the way they are solved in real life today, the educational system will change forever. It is a small policy change that is required. Allow the use of the Internet and collaboration during an examination.
If we did that to exams, the curriculum would have to be different. We would not need to emphasise facts or figures or dates. The curriculum would have to become questions that have strange and interesting answers. “Where did language come from?”, “Why were the pyramids built?”, “Is life on Earth sustainable?”, “What is the purpose of theatre?”. Questions that engage learners in a world of unknowns. Questions that will occupy their minds through their waking hours and sometimes their dreams.
Teaching in an environment where the Internet and discussion are allowed in exams would be different. The ability to find things out quickly and accurately would become the predominant skill. The ability to discriminate between alternatives, then put facts together to solve problems would be critical. That is a skill that future employers would admire immensely.
In this kind of self-organised learning, we do not need the same teachers all the time. Any teacher can cause any kind of learning to emerge. A teacher does not need to be physically present, she could be a projected, life-sized image on the wall.
A Granny Cloud of such volunteer teachers have been operating out of the United Kingdom and a few other countries into schools in India and South America for more than five years.
We do not need to improve schools. We need to reinvent them for our times, our requirements and our future. We do not need efficient clerks to fuel an administrative machine that is no longer needed. Machines will do that for us.
We need people who can think divergently, across outdated disciplines, connecting ideas across the entire mass of humanity. We need people who can think like children. THE GUARDIAN
Dr Sugata Mitra is professor of educational technology at Newcastle University and the winner of the TED Prize this year. He devised the Hole in the Wall experiment, where a computer was embedded in a wall in a slum in New Delhi for children to use freely. He aimed to prove young people could be taught to use computers easily without formal training.
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