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Thick-tissue spatial transcriptomics w/ 3DEEP-HybISS in skin enabled pseudotemporal molecular mapping of hair follicle organogenesis via asynchrony of follicle development: Explore the data for urself: Congrats to Reza Kalhor +team

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Dr. Jean Fan

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12,503 Aufrufe • vor 25 Tagen •via X (Twitter)

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PHOTON COUNTING CT is NOT a better CT It is a NEW imaging modality Photon Counting CT (PCCT) represents a transformative leap in medical imaging, not only as a molecular imaging modality but also as a technology offering ultra-high resolution and functional imaging capabilities. It is fundamentally more than just an enhanced version of traditional CT—PCCT introduces new ways of seeing and understanding the human body, providing critical insights at the molecular, structural, and functional levels. This positions PCCT as a unique imaging modality that requires a fresh approach to technical implementation, operational workflows, and financial planning. Despite the larger upfront investment, PCCT’s ability to drastically reduce downstream healthcare costs makes it a highly valuable investment in the long run. 1. Technical Innovations • Molecular Imaging and Energy Discrimination: Unlike traditional CT, which simply measures the total absorbed energy, PCCT counts individual X-ray photons and differentiates their energy levels. This allows for precise molecular imaging, revealing the composition of tissues and materials at a biochemical level. By distinguishing between different tissue types and contrast agents, PCCT opens up new diagnostic possibilities, such as identifying molecular biomarkers in tumors or distinguishing between stable and unstable plaque in coronary arteries. This capability shifts the focus of imaging from purely anatomical to both anatomical and molecular, offering more comprehensive diagnostic information. • Ultra-High Spatial Resolution: PCCT features significantly smaller detector elements compared to conventional CT scanners, allowing for ultra-high resolution imaging. This means clinicians can visualize fine structures such as microcalcifications in arteries, small lesions in soft tissues, or the intricate architecture of bones. This level of detail was previously unattainable with traditional CT. When combined with molecular imaging, this ultra-high resolution allows for the precise localization and characterization of disease at very early stages, which is essential for early diagnosis and intervention. • Functional Imaging Capabilities: PCCT also excels as a functional imaging modality. By capturing energy-resolved information, PCCT can provide insights into tissue functionality and dynamic physiological processes. For instance, it can detect changes in blood flow, tissue perfusion, and oxygenation without the need for additional contrast agents or scans. This functionality allows for real-time assessment of physiological processes, making it particularly valuable in cardiology, oncology, and neurology for evaluating organ function and monitoring disease progression. • Reduced Noise and Artifact Reduction: Photon-counting technology dramatically reduces electronic noise and imaging artifacts, such as beam hardening, resulting in clearer and more accurate images. The ability to deliver ultra-high resolution images with minimal artifacts improves diagnostic accuracy, reducing the need for repeat scans and ensuring that even subtle abnormalities are detected. 2. Operational Considerations • New Workflow for Molecular, High-Resolution, and Functional Imaging: The integration of molecular, ultra-high resolution, and functional imaging into routine clinical workflows introduces complexity that requires adaptation. Radiologists and technicians need specialized training to interpret and analyze multi-energy datasets that include molecular and functional information. PCCT produces a vast amount of detailed data, requiring clinicians to adopt new imaging protocols and refine their diagnostic approaches to fully leverage its capabilities. • Post-Processing and Data Management: PCCT generates richer, more complex datasets, which necessitates advanced post-processing tools and data management systems. Existing PACS and imaging software may not be equipped to handle such large volumes of data or to process functional and molecular information effectively. This means healthcare institutions must invest in robust IT infrastructure, including upgraded software and storage solutions, as well as provide additional training for staff on new imaging analysis techniques. • Revised Clinical Protocols: The molecular, functional, and ultra-high resolution imaging capabilities of PCCT will likely prompt changes in clinical protocols. For instance, the need for contrast agents may be reduced, simplifying patient preparation and decreasing the risk of adverse reactions. Additionally, the ability to monitor physiological functions in real-time through functional imaging could lead to more dynamic diagnostic procedures, such as assessing the effectiveness of interventions or treatments in real-time. 3. Financial Impact • Higher Initial Investment: PCCT systems are more expensive than traditional CT scanners due to their advanced technology, which includes photon-counting detectors and the computational power required for high-resolution, molecular, and functional imaging. While this upfront cost is significant, it is crucial to view it in the broader context of the downstream benefits and cost reductions that PCCT offers. • Downstream Cost Reductions: Although the initial capital investment is higher, PCCT’s ability to combine molecular, functional, and ultra-high resolution imaging leads to substantial reductions in downstream healthcare costs. Its superior diagnostic accuracy minimizes the need for follow-up tests, repeat scans, or invasive diagnostic procedures, such as diagnostic coronary angiographies. For example, in cardiology, PCCT can precisely differentiate between types of coronary plaque, reducing the need for invasive procedures to assess risk. • Lower Overall Healthcare Expenditures: By enabling earlier, more accurate diagnoses, PCCT can reduce the overall cost of patient care. Early detection of disease, particularly through its molecular and functional imaging capabilities, allows for more targeted treatments, potentially preventing the need for more aggressive and expensive interventions down the line. For instance, early-stage tumor detection via molecular imaging could lead to less invasive treatments, reducing hospital stays and improving patient outcomes, ultimately driving down healthcare costs. • Increased ROI Through Enhanced Patient Outcomes: Over time, the combination of molecular, functional, and ultra-high resolution imaging enhances diagnostic precision, which translates into better patient outcomes. Improved diagnostic accuracy reduces the incidence of unnecessary procedures, minimizes treatment delays, and results in more personalized and effective care. This leads to increased patient satisfaction, better healthcare outcomes, and greater patient throughput—all factors that improve the institution’s return on investment (ROI). • Competitive Advantage and New Revenue Streams: By adopting PCCT, healthcare institutions position themselves at the forefront of advanced imaging technologies. The ability to offer molecular, functional, and ultra-high resolution imaging creates a competitive advantage, attracting more complex and high-value cases. This can boost the institution’s reputation for excellence in diagnostics, leading to increased referrals, new patient populations, and expanded revenue opportunities. Summary Photon Counting CT (PCCT) is not just an evolution of existing CT technology—it is a molecular, ultra-high resolution, and functional imaging modality that fundamentally transforms the diagnostic landscape. Its ability to capture detailed molecular data, visualize minute anatomical structures with ultra-high resolution, and provide real-time functional imaging opens new possibilities for earlier and more precise diagnoses. While the financial investment in PCCT is larger, the reduction in downstream healthcare costs through improved diagnostic accuracy, fewer unnecessary interventions, and earlier disease detection far outweighs the initial expense. For institutions committed to advancing patient care and improving long-term financial outcomes, PCCT is an essential investment in the future of medical imaging. The video attached shows a patient accessing the Hospital for ACS. PCCT can provide ALL the imaging information of the concurrent imaging modalities (CXR, CAG, Echo, CMR) that you see around it... that's a lot! #PhotonCountingCT #MolecularImaging #UltraHighResolution #FunctionalImaging #FutureOfImaging #AdvancedMedicalImaging #EarlyDiseaseDetection #InnovativeCT #CuttingEdgeHealthcare #PrecisionDiagnostics #HealthcareInnovation #MedicalTechnology #CostEffectiveImaging #NextGenCT #PatientCareRevolution
1:10

PHOTON COUNTING CT is NOT a better CT It is a NEW imaging modality Photon Counting CT (PCCT) represents a transformative leap in medical imaging, not only as a molecular imaging modality but also as a technology offering ultra-high resolution and functional imaging capabilities. It is fundamentally more than just an enhanced version of traditional CT—PCCT introduces new ways of seeing and understanding the human body, providing critical insights at the molecular, structural, and functional levels. This positions PCCT as a unique imaging modality that requires a fresh approach to technical implementation, operational workflows, and financial planning. Despite the larger upfront investment, PCCT’s ability to drastically reduce downstream healthcare costs makes it a highly valuable investment in the long run. 1. Technical Innovations • Molecular Imaging and Energy Discrimination: Unlike traditional CT, which simply measures the total absorbed energy, PCCT counts individual X-ray photons and differentiates their energy levels. This allows for precise molecular imaging, revealing the composition of tissues and materials at a biochemical level. By distinguishing between different tissue types and contrast agents, PCCT opens up new diagnostic possibilities, such as identifying molecular biomarkers in tumors or distinguishing between stable and unstable plaque in coronary arteries. This capability shifts the focus of imaging from purely anatomical to both anatomical and molecular, offering more comprehensive diagnostic information. • Ultra-High Spatial Resolution: PCCT features significantly smaller detector elements compared to conventional CT scanners, allowing for ultra-high resolution imaging. This means clinicians can visualize fine structures such as microcalcifications in arteries, small lesions in soft tissues, or the intricate architecture of bones. This level of detail was previously unattainable with traditional CT. When combined with molecular imaging, this ultra-high resolution allows for the precise localization and characterization of disease at very early stages, which is essential for early diagnosis and intervention. • Functional Imaging Capabilities: PCCT also excels as a functional imaging modality. By capturing energy-resolved information, PCCT can provide insights into tissue functionality and dynamic physiological processes. For instance, it can detect changes in blood flow, tissue perfusion, and oxygenation without the need for additional contrast agents or scans. This functionality allows for real-time assessment of physiological processes, making it particularly valuable in cardiology, oncology, and neurology for evaluating organ function and monitoring disease progression. • Reduced Noise and Artifact Reduction: Photon-counting technology dramatically reduces electronic noise and imaging artifacts, such as beam hardening, resulting in clearer and more accurate images. The ability to deliver ultra-high resolution images with minimal artifacts improves diagnostic accuracy, reducing the need for repeat scans and ensuring that even subtle abnormalities are detected. 2. Operational Considerations • New Workflow for Molecular, High-Resolution, and Functional Imaging: The integration of molecular, ultra-high resolution, and functional imaging into routine clinical workflows introduces complexity that requires adaptation. Radiologists and technicians need specialized training to interpret and analyze multi-energy datasets that include molecular and functional information. PCCT produces a vast amount of detailed data, requiring clinicians to adopt new imaging protocols and refine their diagnostic approaches to fully leverage its capabilities. • Post-Processing and Data Management: PCCT generates richer, more complex datasets, which necessitates advanced post-processing tools and data management systems. Existing PACS and imaging software may not be equipped to handle such large volumes of data or to process functional and molecular information effectively. This means healthcare institutions must invest in robust IT infrastructure, including upgraded software and storage solutions, as well as provide additional training for staff on new imaging analysis techniques. • Revised Clinical Protocols: The molecular, functional, and ultra-high resolution imaging capabilities of PCCT will likely prompt changes in clinical protocols. For instance, the need for contrast agents may be reduced, simplifying patient preparation and decreasing the risk of adverse reactions. Additionally, the ability to monitor physiological functions in real-time through functional imaging could lead to more dynamic diagnostic procedures, such as assessing the effectiveness of interventions or treatments in real-time. 3. 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For example, in cardiology, PCCT can precisely differentiate between types of coronary plaque, reducing the need for invasive procedures to assess risk. • Lower Overall Healthcare Expenditures: By enabling earlier, more accurate diagnoses, PCCT can reduce the overall cost of patient care. Early detection of disease, particularly through its molecular and functional imaging capabilities, allows for more targeted treatments, potentially preventing the need for more aggressive and expensive interventions down the line. For instance, early-stage tumor detection via molecular imaging could lead to less invasive treatments, reducing hospital stays and improving patient outcomes, ultimately driving down healthcare costs. • Increased ROI Through Enhanced Patient Outcomes: Over time, the combination of molecular, functional, and ultra-high resolution imaging enhances diagnostic precision, which translates into better patient outcomes. Improved diagnostic accuracy reduces the incidence of unnecessary procedures, minimizes treatment delays, and results in more personalized and effective care. This leads to increased patient satisfaction, better healthcare outcomes, and greater patient throughput—all factors that improve the institution’s return on investment (ROI). • Competitive Advantage and New Revenue Streams: By adopting PCCT, healthcare institutions position themselves at the forefront of advanced imaging technologies. The ability to offer molecular, functional, and ultra-high resolution imaging creates a competitive advantage, attracting more complex and high-value cases. This can boost the institution’s reputation for excellence in diagnostics, leading to increased referrals, new patient populations, and expanded revenue opportunities. Summary Photon Counting CT (PCCT) is not just an evolution of existing CT technology—it is a molecular, ultra-high resolution, and functional imaging modality that fundamentally transforms the diagnostic landscape. Its ability to capture detailed molecular data, visualize minute anatomical structures with ultra-high resolution, and provide real-time functional imaging opens new possibilities for earlier and more precise diagnoses. While the financial investment in PCCT is larger, the reduction in downstream healthcare costs through improved diagnostic accuracy, fewer unnecessary interventions, and earlier disease detection far outweighs the initial expense. For institutions committed to advancing patient care and improving long-term financial outcomes, PCCT is an essential investment in the future of medical imaging. The video attached shows a patient accessing the Hospital for ACS. PCCT can provide ALL the imaging information of the concurrent imaging modalities (CXR, CAG, Echo, CMR) that you see around it... that's a lot! #PhotonCountingCT #MolecularImaging #UltraHighResolution #FunctionalImaging #FutureOfImaging #AdvancedMedicalImaging #EarlyDiseaseDetection #InnovativeCT #CuttingEdgeHealthcare #PrecisionDiagnostics #HealthcareInnovation #MedicalTechnology #CostEffectiveImaging #NextGenCT #PatientCareRevolution

Dr. Filippo Cademartiri

11,820 Aufrufe • vor 1 Jahr

Introducing WorldView 3D, a first-of-its-kind satellite tasking product that delivers up-to-date 3D ground truth anywhere on Earth. From GPS-denied autonomy and intelligence analysis to consumer-grade mapping and disaster response, the world's most important missions increasingly depend on accurate, up-to-date 3D terrain. But for years, keeping 3D maps current at global scale hasn't been possible. WorldView 3D changes that. Built on Vantor’s trusted spatial foundation, our new tasking capability empowers customers to task and receive updated 3D data within 24 hours of image collection. For missions that require greater fidelity, they can also produce high-definition 3D maps anywhere in the world. 3D is the future of spatial intelligence, and Vantor is leading the change. Our trusted spatial foundation already includes 100 million sq km of the world mapped inhighly accurate 3D. Now customers can update the locations that matter most with the speed, scale, and fidelity required for critical missions. Read the full announcement:
0:35

Introducing WorldView 3D, a first-of-its-kind satellite tasking product that delivers up-to-date 3D ground truth anywhere on Earth. From GPS-denied autonomy and intelligence analysis to consumer-grade mapping and disaster response, the world's most important missions increasingly depend on accurate, up-to-date 3D terrain. But for years, keeping 3D maps current at global scale hasn't been possible. WorldView 3D changes that. Built on Vantor’s trusted spatial foundation, our new tasking capability empowers customers to task and receive updated 3D data within 24 hours of image collection. For missions that require greater fidelity, they can also produce high-definition 3D maps anywhere in the world. 3D is the future of spatial intelligence, and Vantor is leading the change. Our trusted spatial foundation already includes 100 million sq km of the world mapped inhighly accurate 3D. Now customers can update the locations that matter most with the speed, scale, and fidelity required for critical missions. Read the full announcement:

Vantor

16,030 Aufrufe • vor 26 Tagen

Google presents Still-Moving Customized Video Generation without Customized Video Data Customizing text-to-image (T2I) models has seen tremendous progress recently, particularly in areas such as personalization, stylization, and conditional generation. However, expanding this progress to video generation is still in its infancy, primarily due to the lack of customized video data. In this work, we introduce Still-Moving, a novel generic framework for customizing a text-to-video (T2V) model, without requiring any customized video data. The framework applies to the prominent T2V design where the video model is built over a text-to-image (T2I) model (e.g., via inflation). We assume access to a customized version of the T2I model, trained only on still image data (e.g., using DreamBooth or StyleDrop). Naively plugging in the weights of the customized T2I model into the T2V model often leads to significant artifacts or insufficient adherence to the customization data. To overcome this issue, we train lightweight Spatial Adapters that adjust the features produced by the injected T2I layers. Importantly, our adapters are trained on "frozen videos" (i.e., repeated images), constructed from image samples generated by the customized T2I model. This training is facilitated by a novel Motion Adapter module, which allows us to train on such static videos while preserving the motion prior of the video model. At test time, we remove the Motion Adapter modules and leave in only the trained Spatial Adapters. This restores the motion prior of the T2V model while adhering to the spatial prior of the customized T2I model. We demonstrate the effectiveness of our approach on diverse tasks including personalized, stylized, and conditional generation. In all evaluated scenarios, our method seamlessly integrates the spatial prior of the customized T2I model with a motion prior supplied by the T2V model.
1:43

Google presents Still-Moving Customized Video Generation without Customized Video Data Customizing text-to-image (T2I) models has seen tremendous progress recently, particularly in areas such as personalization, stylization, and conditional generation. However, expanding this progress to video generation is still in its infancy, primarily due to the lack of customized video data. In this work, we introduce Still-Moving, a novel generic framework for customizing a text-to-video (T2V) model, without requiring any customized video data. The framework applies to the prominent T2V design where the video model is built over a text-to-image (T2I) model (e.g., via inflation). We assume access to a customized version of the T2I model, trained only on still image data (e.g., using DreamBooth or StyleDrop). Naively plugging in the weights of the customized T2I model into the T2V model often leads to significant artifacts or insufficient adherence to the customization data. To overcome this issue, we train lightweight Spatial Adapters that adjust the features produced by the injected T2I layers. Importantly, our adapters are trained on "frozen videos" (i.e., repeated images), constructed from image samples generated by the customized T2I model. This training is facilitated by a novel Motion Adapter module, which allows us to train on such static videos while preserving the motion prior of the video model. At test time, we remove the Motion Adapter modules and leave in only the trained Spatial Adapters. This restores the motion prior of the T2V model while adhering to the spatial prior of the customized T2I model. We demonstrate the effectiveness of our approach on diverse tasks including personalized, stylized, and conditional generation. In all evaluated scenarios, our method seamlessly integrates the spatial prior of the customized T2I model with a motion prior supplied by the T2V model.

AK

40,474 Aufrufe • vor 2 Jahren

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning
1:11

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning

Alex Ratner

495,851 Aufrufe • vor 1 Jahr