MIT is one of the world’s premier research universities, responsible for all manner of innovative and exciting developments since their founding in 1861. Now MIT researchers have developed a machine-learning algorithm that registers 3D images (like brain scans) 1000-plus times more quickly than traditional methods.
Traditionally, 3D images are created via a technique called medical image registration. This process overlays two images, like MRIs, to compare and contrast anatomical information in great detail – an especially useful tool for doctors to gauge progress with a patient or treatment.
MRI (magnetic resonance imaging) scans consist of hundreds of 2D images, all stacked on top of each other to form 3D images. These images, called “volumes”, contain millions of pixels, or “voxels”. Aligning voxels from multiple volumes is a complex process, made more so by variables like spatial orientations and machine types. Adrian Dalca, a postdoc at Massachusetts General Hospital and CSAIL and co-author of the paper, describes it as “wiggling” the images until the images fit each other. “Mathematically, this optimization procedure takes a long time,” said Dalca – potentially hundreds of hours, if analyzing scans from large populations of data.
This delay is because the algorithms involved never learn from the information they analyze, instead of dismissing all data regarding voxel location after each pair of images. The new algorithm, VoxelMorph, corrects this flaw, registering information from thousands of pairs of images – “Information you should be able to carry over,” explained Guha Balakrishnan, an MIT grad student, and paper co-author – to learn how to align images and estimate optimal alignment parameters. Once the algorithm “learns”, it maps all pixels from one image to another at once, vastly reducing registration times to a couple of minutes via a standard computer.
VoxelMorph uses a common machine-learning approach called a CNN or convolutional neural network. The CNN network is augmented by a spatial transformer, which captures similarities in voxels between MRI scans. It learns from groups of voxels, which it then uses to develop optimized parameters that can be used on any scan pair. All information is gathered in the training phase, with future registrations executed using a single, easily-computed function evaluation.
Another benefit to VoxelMorph is the data is “unsupervised” – it does not require additional information beyond image data to make an accurate reading. Each registration is “smooth”, or without any image distortion or holes, and can be calculated within roughly two minutes via a traditional CPU, or under a second with a graphics processing unit.
Enhanced speed opens a variety of potential application – scanning other parts of the body, for example, or using image registration in close to real-time. The result is a better experience for patients and a powerful tool in doctors’ pockets, all thanks to machine learning.
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Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
The 10-day moving average for ELV crossed bearishly below the 50-day moving average on October 02, 2026. This indicates that the trend has shifted lower and could be considered a sell signal. In 11 of 15 past instances when the 10-day crossed below the 50-day, the stock continued to move higher over the following month. The odds of a continued downward trend are 73%.
The Momentum Indicator moved below the 0 level on September 24, 2026. You may want to consider selling the stock, shorting the stock, or exploring put options on ELV as a result. In 53 of 96 cases where the Momentum Indicator fell below 0, the stock fell further within the subsequent month. The odds of a continued downward trend are 55%.
The Moving Average Convergence Divergence Histogram (MACD) for ELV turned negative on September 21, 2026. This could be a sign that the stock is set to turn lower in the coming weeks. Traders may want to sell the stock or buy put options. Tickeron's A.I.dvisor looked at 49 similar instances when the indicator turned negative. In 26 of the 49 cases the stock turned lower in the days that followed. This puts the odds of success at 53%.
Following a 3-day decline, the stock is projected to fall further. Considering past instances where ELV declined for three days, the price rose further in 50 of 62 cases within the following month. The odds of a continued downward trend are 56%.
ELV broke above its upper Bollinger Band on September 14, 2026. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options.
The RSI Oscillator points to a transition from a downward trend to an upward trend -- in cases where ELV's RSI Indicator exited the oversold zone, 15 of 23 resulted in an increase in price. Tickeron's analysis proposes that the odds of a continued upward trend are 65%.
The Stochastic Oscillator suggests the stock price trend may be in a reversal from a downward trend to an upward trend. 38 of 64 cases where ELV's Stochastic Oscillator exited the oversold zone resulted in an increase in price. Tickeron's analysis proposes that the odds of a continued upward trend are 59%.
ELV moved above its 50-day moving average on October 06, 2026 date and that indicates a change from a downward trend to an upward trend.
Following a +3.54% 3-day Advance, the price is estimated to grow further. Considering data from situations where ELV advanced for three days, in 184 of 323 cases, the price rose further within the following month. The odds of a continued upward trend are 57%.
The Aroon Indicator entered an Uptrend today. In 131 of 231 cases where ELV Aroon's Indicator entered an Uptrend, the price rose further within the following month. The odds of a continued Uptrend are 57%.
The Tickeron Valuation Rating of 6 (best 1 - 100 worst) indicates that the company is seriously undervalued in the industry. This rating compares market capitalization estimated by our proprietary formula with the current market capitalization. This rating is based on the following metrics, as compared to industry averages: P/B Ratio (1.907) is normal, around the industry mean (3.247). P/E Ratio (17.452) is within average values for comparable stocks, (139.958). ELV's Projected Growth (PEG Ratio) (1.291) is slightly higher than the industry average of (0.786). Dividend Yield (0.017) settles around the average of (0.009) among similar stocks. P/S Ratio (0.453) is also within normal values, averaging (0.569).
The Tickeron PE Growth Rating for this company is 18 (best 1 - 100 worst), pointing to outstanding earnings growth. The PE Growth rating is based on a comparative analysis of stock PE ratio increase over the last 12 months compared against S&P 500 index constituents.
The Tickeron Price Growth Rating for this company is 46 (best 1 - 100 worst), indicating steady price growth. ELV’s price grows at a higher rate over the last 12 months as compared to S&P 500 index constituents.
The Tickeron Profit vs. Risk Rating rating for this company is 85 (best 1 - 100 worst), indicating that the returns do not compensate for the risks. ELV’s unstable profits reported over time resulted in significant Drawdowns within these last five years. A stable profit reduces stock drawdown and volatility. The average Profit vs. Risk Rating rating for the industry is 88, placing this stock better than average.
The Tickeron SMR rating for this company is 99 (best 1 - 100 worst), indicating weak sales and an unprofitable business model. SMR (Sales, Margin, Return on Equity) rating is based on comparative analysis of weighted Sales, Income Margin and Return on Equity values compared against S&P 500 index constituents. The weighted SMR value is a proprietary formula developed by Tickeron and represents an overall profitability measure for a stock.
The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows
a provider of life, hospital and medical insurance plans
Industry ManagedHealthCare