Image Analysis

Building density, not trees, was strongest predictor of home loss in los angeles firestorms, finds new Cal Poly study

GMO pictures may reinforce existing views, deepening the divide

A new study published in JCOM finds that images of GMOs tend to reinforce pre-existing attitudes, amplifying polarization rather than changing minds. The study used a representative sample of the US population and found that even positive images could make people who already supported GMOs more positive, while making skeptics and uncer...

As worms and jellyfish wriggle, new AI tools track their neurons

Three new neural network-based tools enable precise tracking of neurons in worms and jellyfish, overcoming visibility challenges. The tools have been applied to the study of brain activity in C. hemisphaerica jellyfish, allowing researchers to extract neural activity data from videos of the animals.

How rice plants tell head from toe during early growth

A team of scientists from Tokyo Metropolitan University discovered how fertilized rice seeds begin to divide and establish their body axis. They found that the process involves radical steps different from Arabidopsis, with cells acting collectively to allow axis development despite apparent randomness.

Eye for trouble: Automated counting for chromosome issues under the microscope

A machine-learning-based algorithm developed by Tokyo Metropolitan University researchers can accurately count sister chromatid exchanges (SCEs) in chromosomes, giving a more objective measurement. The accuracy rate is 84%, which could help diagnose disorders like Bloom syndrome with greater consistency.

AI tool spots blood cell abnormalities missed by doctors

Researchers have developed a system called CytoDiffusion that uses generative AI to study the shape and structure of blood cells. The system can accurately identify normal blood cell appearances and spot unusual or rare cells that may indicate disease, outperforming existing systems in tests.

Hundreds of animal studies on brain damage after stroke flagged for problematic images

A study has identified over 240 scientific publications with potentially problematic images, casting doubt on the validity of these studies. The findings highlight the need for journals and publishers to investigate image-related issues carefully to ensure the trustworthiness of animal-based research in this field.

AI-based method accurately segments and quantifies overlapping cell membranes

Researchers developed DeMemSeg, an AI-driven pipeline that accurately segments overlapping membrane structures with accuracy comparable to expert manual analysis. The approach enables large-scale, objective, and quantitative analysis of morphological data, providing a foundational technology for advancing disease mechanisms.

3 million cells per minute: parallel microdevice with AI-powered single-cell analysis

Researchers developed a parallel microdevice that combines high-throughput intracellular delivery with automated single-cell image cytometry using AI. The device can deliver gene-silencing RNA and plasmid DNA across multiple cell types, enabling broad utility for cell engineering and personalized therapies.

Cancer therapies: AI-based image analysis detects early organ damage

Researchers at TUM developed an AI-powered algorithm to predict kidney damage in prostate cancer patients undergoing lutetium-177 PSMA therapy. Early detection could enable personalized treatment adjustments to prevent organ damage.

BiaPy, an accessible AI tool for analysing biomedical images

BiaPy breaks down the barrier to AI-based image analysis in biomedicine, allowing more scientists and healthcare professionals to harness its potential. The tool offers various types of analysis, including cell identification, element counting, and improving image quality, on both two-dimensional and three-dimensional images.

ODEP-based robotic system for micromanipulation and in-flow analysis of primary cells

A new robotic system utilizes optically-induced dielectrophoresis (ODEP) for the classification and analysis of patient-derived endometrial stromal cells. The system enables precise micromanipulation and measurement of single cells, providing insights into cell properties and responses to nonuniform electric fields.

Unveiling the 3D crystal secrets of defective nanoparticles

Researchers at JAIST have developed a low-dose imaging technique that maps the three-dimensional atomic structure of titanium oxyhydroxide nanoparticles without damaging them. This breakthrough enables safer analysis and opens possibilities for designing materials with enhanced functionality.

Towards understanding tumors in 3D

Researchers mapped a lung tumor's cellular neighborhoods in 3D using single-cell spatial technologies, identifying 18 cell types and potential targets for personalized cancer therapy. The study reveals new insights into how tumor cells interact with their surroundings and how to reverse immune suppression mechanisms.

Estimating complex immune cell structures by AI tools for survival prediction in advanced melanoma

Researchers used AI-driven methods to analyze thousands of digital images of melanoma tumor tissue, identifying key immune cell structures that boost immunotherapy effects. The presence of these structures was linked to significantly better overall survival for patients with advanced melanoma.

Helping computers perceive and interact with the visual world

Schmid's contributions have helped computers recognize complex objects, understand video analysis, and process realistic settings. Her leadership has built active research communities, mentoring and supervising peers across the field of computer vision.

Brain-inspired AI breakthrough: making computers see more like humans

A team of researchers developed Lp-Convolution, a novel method that uses multivariate p-generalized normal distribution to reshape CNN filters dynamically. This breakthrough improves the accuracy and efficiency of image recognition systems while reducing computational burden.

Smartphone eye photos may help detect anemia in children

Researchers developed a new method that uses simple grayscale eye photos to predict anemia in children. The technique analyzes patterns and textures in the conjunctiva of the eye, avoiding problems caused by different light conditions or camera models.

Scientists can tell healthy and cancerous cells apart by how they move

Researchers at Tokyo Metropolitan University have created a novel technique using phase-contrast microscopy to track and analyze the motion of unlabeled cells. This allows for the accurate differentiation of cancerous cells with up to 94% accuracy, opening new avenues for diagnosis and research on cell motility related functions.

New study unveils volcanic history and clues to ancient life on Mars

A new study by Texas A&M University researchers has revealed insights into Mars' geological history and potential for ancient life. The team analyzed diverse volcanic rocks in the Jezero Crater, providing a window into the planet's distant past and signs of altered olivine.

New evidence suggesting magnetar origin of GRBs

A new study finds that a millisecond magnetar could have triggered the flashes of GRB 230307A, an extremely bright GRB detected in March 2023. The observation suggests that the magnetar model is consistent with the features of the prompt emission and the long-lasting X-ray plateau.

A visual pathway in the brain may do more than recognize objects

MIT researchers have found that a computational model of the ventral stream, which processes object recognition, also performs well on spatial tasks such as determining an object's location and orientation. This challenges the dominant perspective that the ventral stream is optimized for object recognition.

Microscopy method breaks barriers in nanoscale chemical imaging

A new microscopy technique, SIMIP, combines structured illumination with mid-infrared photothermal detection to achieve high-speed chemical imaging with superior resolution. The method outperforms conventional methods in terms of spatial resolution and chemical contrast.

New projections reveal more extreme erosion on O’ahu’s shores

A new study reveals that 81% of O’ahu's coastline could experience erosion by 2100, with a further 40% loss happening by 2030. The research used computer models incorporating satellite imagery to predict the seasonal movement of sand, resulting in more severe erosion projections than previous studies.

New system for the early detection of autism

A new system for early detection of Autism Spectrum Disorder (ASD) has been developed using virtual reality and artificial intelligence. The system, which uses biomarkers related to behavior, motor activity, and gaze direction, achieves an accuracy of over 85%, surpassing traditional methods.

AI tool can track effectiveness of multiple sclerosis treatments

A new AI tool called MindGlide can extract key information from brain images to measure damaged areas and highlight subtle changes in MS patients. The tool performed better than other AI tools and expert clinical analysis, enabling researchers to unlock valuable insights into multiple sclerosis.

Rare combination of ovarian tumors found in one patient

A new case report presents a highly unusual combination of two benign ovarian tumors: serous cystadenofibroma and collision lesions. Accurate preoperative diagnosis is critical for effective treatment planning, and this case emphasizes the need for personalized evaluation of each ovarian mass.

China’s Chang’e-6 returned lunar samples reveal differences in space environment in the Moon’s near and far side

The study found that solar wind radiation plays a dominant role in space weathering on the lunar farside, differing from the nearside. The Chang'e-6 samples showed less melt drops and no nanophase metallic iron particles, indicating variations in the space environment.

The experts that can outsmart optical illusions

Researchers found that medical imaging experts can solve common optical illusions, including judging the size of objects. Training to improve visual perception can also make experts less susceptible to these illusions. This study has implications for training medical image analysts.

AI is as good as pathologists at diagnosing celiac disease, study finds

A machine learning algorithm has been developed to diagnose coeliac disease with high accuracy, outperforming human pathologists in over 97 cases. The AI tool has the potential to speed up diagnosis and reduce delays in receiving an accurate diagnosis for patients suffering from this autoimmune disease.

New geospatial intelligence methodology makes land use management more accurate and faster

Researchers developed a new geospatial intelligence methodology to accurately delineate areas of natural vegetation and agricultural production by crop type. The results showed 95% accuracy in mapping, providing support for public policies aimed at agricultural production and environmental conservation.

Linking diet, lifestyle & telomere length: insights from NHANES data

A study using NHANES data found that inflammation, rather than diet and exercise, has the strongest association with telomere shortening. Managing chronic inflammation may be key to preserving telomere length and promoting healthy aging.

Developing a clearer understanding of permafrost thaw risk in Alaska

Researchers developed a method that uses high-resolution satellite imagery and deep machine learning to double the mapped infrastructure of Alaska, more accurately projecting economic risks associated with permafrost thaw. The new model nearly doubles the amount of information available for Alaska on OpenStreetMap.

High-precision full waveform inversion imaging and its applications

Full Waveform Inversion (FWI) technology provides unprecedented precision in seismic imaging, breaking resolution limitations of traditional methods. It characterizes complex structures within the Earth's interior and offers higher-resolution subsurface models.

“ChatGPT” for computer security

A team led by Dr. Marcus Botacin is creating a large language model (LLM) to automatically identify malware and write rules to defend against it. The LLM will use signatures to complement human analysts' skills, identifying malware faster and more accurately.

Breakthrough in materials science: AI reveals secrets of dendritic growth in thin films

A new AI model developed by Tokyo University of Science's researchers predicts dendritic growth in thin films, offering a powerful pathway for optimizing thin-film fabrication. The model analyzes morphology using persistent homology and machine learning with energy analysis, revealing conditions that drive branching behavior.

‘Democratizing chemical analysis’: FSU chemists use machine learning and robotics to identify chemical compositions from images

Researchers developed a simple, inexpensive tool using robotics and artificial intelligence to analyze dried salt solutions from images. The method increases the accuracy of chemical analysis in scenarios where large samples are difficult to obtain, making it valuable for space exploration, law enforcement, and hospital use.

Deep learning revolutionizes cytoskeleton research

A research team at Kumamoto University developed a deep learning-based method for analyzing the cytoskeleton more accurately and efficiently than ever before. This technique enabled more reliable measurements of cytoskeleton density, which is critical for understanding cellular structure and function.

Study explores effects of climatic changes on Christmas Island’s iconic red crabs

A new study by the University of Plymouth investigated the effect of changing global climate conditions on Christmas Island's red crab embryos. The researchers found that lower salinity levels did not delay embryonic development, but emphasized the need for further research to understand the species' response to environmental stressors.

Combating deepfakes with CAPTCHA-like verification for GenAI video

CHARCHA, developed by Carnegie Mellon University and MIT researchers, uses real-time physical interactions to verify user identity in generative video content. The system prevents unauthorized deepfakes and gives users greater control over their likeness.

Satellite image analysis delivers new insight into the functional diversity of tropical forests

Researchers analyzed satellite data from the Sentinel-2 satellites to predict variations in tree traits and map functional diversity. They found significant differences in forest function across continents, with American tropical forests showing greater functional richness than African and Asian forests.

Study reveals how agave plants survive extreme droughts

Researchers used terahertz spectroscopy to study agave plants' ability to retain water in dry environments. They found that agaves store water in a specialized leaf structure and fructans act like molecular sponges to retain moisture. This discovery could lead to better farming practices and drought-resistant crops

AI revolutionizes glaucoma care: Tohoku University develops specialist-level screening system

The AI-GS network achieves high accuracy with 93.52% sensitivity at 95% specificity, excelling in detecting early-stage glaucoma. The system is portable, requiring minimal computational power and delivering results in under a second.

Deep-learning framework advances tissue analysis in spatial transcriptomics

Researchers developed a deep-learning framework, STAIG, to automatically map distinct genetic activity to tissue regions without manual alignment. The study demonstrates superior performance across various conditions, showcasing its potential for cancer research and understanding complex biological systems.

A versatile AI system for analyzing series of medical images

A new AI-based system called LILAC can accurately detect changes and predict outcomes in various medical applications. The system has been demonstrated on diverse longitudinal image series covering IVF embryos, healing tissue after wounds, and aging brains.

Deep learning in the diagnosis and prognosis of oral potentially malignant disorders

This study utilized deep learning models to diagnose and predict the likelihood of malignant transformation in oral potentially malignant disorders. AI-driven approaches offer noninvasive, cost-effective, and objective means to enhance early detection and improve patient outcomes.

Automatic cell analysis with the help of artificial intelligence

An international research team developed a user-friendly software method called Segment Anything for Microscopy, which can precisely segment images of tissues, cells, and similar structures. The new model improved performance for cell segmentation, enabling researchers to automate tasks that previously took weeks of manual effort.

Viking skulls reveal severe morbidity

A study of Viking skulls using CT scans reveals a range of diseases including sinus and ear infections, osteoarthritis, and dental diseases. The results provide greater understanding of the health and wellbeing of the Viking population.

Politecnico di Milano and Georgia Tech unveil new scenarios for asteroid deflection

Researchers from Politecnico di Milano and Georgia Tech analyzed NASA's DART mission to asteroid Dimorphos, revealing a viable mechanism for ejecta evolution and understanding the impact of an asteroid's shape on deflection. The studies suggest that sending multiple smaller impactors can increase the asteroid push while reducing costs.

Butterfly wings inspire new imaging technique for cancer diagnosis

Researchers have created a new imaging technique that uses the nanostructures found on butterfly wings to analyze cancerous tissues, providing a simpler and more accessible tool for cancer diagnosis. The method has shown comparable results to conventional staining methods and advanced imaging techniques, offering a stain-free alternative.

Innovative technology enhances cellular and molecular insights into kidney lesions

A new method combines traditional histopathology with spatial transcriptomics data to improve understanding of chronic kidney disease lesions at the cellular and molecular levels. This approach has the potential to identify new biomarkers and therapeutic strategies for patients.

Kahramanmaraş earthquake study showcases potential slip rate errors

Researchers used Synthetic Aperture Radar satellites to quantify off-fault damage and surface displacement caused by the two 2023 earthquakes. The study suggests that off-fault damage can reach up to five kilometers from the fault, contradicting previous estimates.

Computer vision enhances the potential of ultrabroadband imaging in non-destructive testing

Researchers developed a synergetic strategy combining millimeter-wave-terahertz-infrared photo-monitoring and computer-vision three-dimensional modeling for ubiquitous non-destructive inspections. The approach allows for material composition identifications and structural reconstructions of composite multi-layered objects.

Researchers develop a five-minute quality test for sustainable cement industry materials

Researchers developed a five-minute quality test for sustainable cement industry materials, reducing testing time from seven days to just five minutes. The test uses colorimetry and camera technology for real-time quality control of calcined clays, which can partially replace ordinary Portland cement.

YOLO-Behavior: A new and faster way to extract animal behaviors from video

A new computer vision framework, YOLO-Behavior, automatically identifies animal behaviors from videos, overcoming manual annotation limitations. The method has been applied to various study systems, doubling available data for parental care behavior and enabling rapid analysis of cooperative behavior.

Researchers identify a brain circuit for creativity

A new study led by researchers at Mass General Brigham suggests that different brain regions activated by creative tasks are part of one common brain circuit. People with brain injuries or neurodegenerative diseases may have increased creativity due to changes in this circuit.

Age, burial environment don’t hinder soft tissue preservation in dinosaurs

Researchers at North Carolina State University found that soft tissue preservation in fossils does not seem to depend on the species, age or burial environment. The team was able to retrieve vessels from six dinosaur specimens, including four Tyrannosaurus rex and one Brachylophosaurus canadensis, using a suite of analytical tools.

How neighborhood perception affects housing rents: A novel analytical approach

A new method developed by Osaka Metropolitan University accurately predicts housing prices in Osaka City, with neighborhood perception being a key factor. The approach achieves nearly 75% accuracy by combining existing property data with machine-learning-processed street view images.

Pennington Biomedical contributes to study advancing medical imaging on body fat and muscle distribution

A recent study introduces an innovative method for analyzing body composition, providing accurate assessments of body fat and muscle distribution. The approach utilizes deep, nonlinear methods to enhance estimation accuracy, surpassing previous linear models.

Texas A&M researcher awarded NASA grant to study Martian dunes

Lauren Berger, a Texas A&M University doctoral student, has been awarded a prestigious FINESST grant from NASA to study Martian dunes. She aims to analyze the shapes and patterns of compound dunes on Mars using high-resolution images, comparing them to similar dunes on Earth.