In recent years, non-destructive imaging technology has made rapid advancements in the field of painting research and preservation. Among these, macro X-ray fluorescence (MA-XRF) analysis stands out, helping experts identify pigments and analyze painting techniques, providing valuable insights into the artist's creative process. However, MA-XRF technology generates large and complex datasets that challenge traditional data analysis methods. Recently, Italian researchers applied deep learning algorithms to spectral analysis of MA-XRF datasets, developing a brand new analysis approach.

Meitu Inc.'s financial report for the first half of 2024 shows a total revenue of 1.62 billion yuan, a year-over-year increase of 28.6%, with an adjusted net profit of 270 million yuan, representing an 80.3% growth. The increase in revenue and net profit is mainly attributed to the advancement of generative AI technology, particularly in the application of imaging and design products. Subscription revenue reached 930 million yuan, reflecting a year-over-year growth of 54.5%, accounting for 57.4% of total revenue. As of June 30, the number of paid subscribers exceeded 10.81 million, with a penetration rate of approximately 4.2%. Meitu's Design Studio focuses on e-commerce design.

"MedTrinity-25M" is a large-scale multimodal medical dataset released by the UCSC-VLAA team, containing 25 million medical images along with detailed annotations. This dataset features multi-granularity annotations, supports the training of multimodal large medical models, and involves a complex construction process that includes data processing, metadata extraction, region of interest localization, and the collection of medical knowledge. Detailed descriptions are generated using large-scale language models to enhance data usability. The dataset was officially released on July 21, 2024, accompanied by a pre-trained model.

MedSAM-2, based on the Segment Anything Model 2 (SAM2) framework, brings revolutionary changes to the field of medical image segmentation. Its core breakthrough treats 2D and 3D images as video sequences, enabling efficient segmentation of three-dimensional images. The 'one-click segmentation' feature allows users to specify a target in a single image, and the model can automatically recognize and accurately segment the same type of object in subsequent images without the need for continuous input. As a general model, it can handle any image.

Perceptive has developed the world's first fully automated AI robot dentist, successfully performing the first complete dental surgery on human patients at a speed 8 times faster than that of human doctors. This innovation introduces the OCT3D imaging system, which uses optical coherence tomography technology to generate 3D images of the inside of teeth, providing high resolution and precise location accuracy, superior to traditional X-rays, and without radiation hazards. The motion structure method adopted by Perceptive addresses the issue of image blurriness, achieving pathological localization accuracy of 20 microns.

The Xiaomi 14 Ultra has been released, featuring AI large model imaging technology, starting at 6499 Yuan. It targets the high-end market, utilizing Xiaomi's Dragon Armor architecture and Jinsha River battery technology to support satellite communication systems and various innovative functions.

🐶 Studies have proven the accuracy of AI and thermal imaging technology in screening for subcutaneous and dermal masses in dogs. 🔬 Research by HT Vista conducted two phases of validation using machine learning algorithms. 🏥 This innovative system is expected to serve as an auxiliary diagnostic tool, aiding in early cancer detection.

By 2035, the number of medical imaging AI tools approved by the FDA is expected to skyrocket, with venture capital support exceeding $30 billion. Over the past seven years, the availability of medical imaging AI products has continued to grow, with medical imaging accounting for 85% of digital health venture capital. Research indicates a strong correlation between venture capital support and the development of AI products, with an estimated 350 new products expected to enter the market by 2035.

The global AI medical imaging market is projected to reach $29.8 billion by 2032. North America holds the largest market share, but the Asia-Pacific region is expected to grow the fastest. Applications of artificial intelligence in radiology and the demand for CT scans are driving market growth. Deep learning and computer vision are the primary technologies, with breast imaging and orthopedic applications being dominant.

OBIA includes 937 patients and 1.93 million medical images from the 301 Hospital, covering 9 modalities and 30 anatomical sites. OBIA realizes the de-identification, management, and quality control of imaging data, providing users with browsing, retrieval, and download services. OBIA fills the gap in the open sharing of biomedical imaging data in the country and helps promote the development of medical imaging AI.