Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

Updated with sections on structural heart echo. Walks through the steps for TAVR, mTEER, and tTEER. This includes 3D models as well as simulated 2D ultrasound images. Would appreciate feedback and suggestions for improvement!

David Ouyang, MD

6,044 subscribers

17,098 görüntüleme • 15 gün önce •via X (Twitter)

Sağlık & İyilik Bilim & Teknoloji

Anya Rossi• Live Now

Private livecam show

4 Yorum

dillon profil fotoğrafı

dillon15 gün önce

This is awesome. I typically try to find something on YouTube for my CRNAs or students to do intraop teaching. Keep them coming. Also I had agents set up a docsthatship website I’ll have it added. What’s your stack? Follow me back and they will DM you

xiaogang zhu profil fotoğrafı

xiaogang zhu15 gün önce

NICE. Thank you for sharing.

Boardy profil fotoğrafı

Boardy15 gün önce

give the alignment step its own chapter

Abdirahman ALI profil fotoğrafı

Abdirahman ALI15 gün önce

awesome

Benzer Videolar

Introducing SAM 3D, the newest addition to the SAM collection, bringing common sense 3D understanding of everyday images. SAM 3D includes two models: 🛋️ SAM 3D Objects for object and scene reconstruction 🧑‍🤝‍🧑 SAM 3D Body for human pose and shape estimation Both models achieve state-of-the-art performance transforming static 2D images into vivid, accurate reconstructions. 🔗 Learn more:

Introducing SAM 3D, the newest addition to the SAM collection, bringing common sense 3D understanding of everyday images. SAM 3D includes two models: 🛋️ SAM 3D Objects for object and scene reconstruction 🧑‍🤝‍🧑 SAM 3D Body for human pose and shape estimation Both models achieve state-of-the-art performance transforming static 2D images into vivid, accurate reconstructions. 🔗 Learn more:

AI at Meta

862,051 görüntüleme • 11 ay önce

I built an interactive echocardiography tutorial with Claude Code. Chapter 07: a 3D heart, the standard imaging views, the probe position, and simulated ultrasound video.

I built an interactive echocardiography tutorial with Claude Code. Chapter 07: a 3D heart, the standard imaging views, the probe position, and simulated ultrasound video.

David Ouyang, MD

108,740 görüntüleme • 1 ay önce

3D renders (and images) based on a 2D drawing, editable in real-time. Incredible. This could be the ChatGPT for 3D assets ↓

3D renders (and images) based on a 2D drawing, editable in real-time. Incredible. This could be the ChatGPT for 3D assets ↓

AI Breakfast

460,111 görüntüleme • 3 yıl önce

I scrubbed through this for all you puzzle solvers. I intentionally left in the area at the top with the clock and battery/wifi as the images were up there as well. ✌️

I scrubbed through this for all you puzzle solvers. I intentionally left in the area at the top with the clock and battery/wifi as the images were up there as well. ✌️

Spaceshot76

23,264 görüntüleme • 7 ay önce

[Rust] New 𝐌𝐚𝐢𝐧 𝐌𝐞𝐧𝐮 The all new overhauled menu is now out on staging for testing and feedback. It includes a completely remade UI as well as additional features like a skin viewer, searchable settings and much more! Quick peek:

[Rust] New 𝐌𝐚𝐢𝐧 𝐌𝐞𝐧𝐮 The all new overhauled menu is now out on staging for testing and feedback. It includes a completely remade UI as well as additional features like a skin viewer, searchable settings and much more! Quick peek:

cipeaX

105,703 görüntüleme • 1 yıl önce

I wanted to test Astra on a 2D game with fluids/water effects, and it did extremely well on the art style, fluid dynamics, and the combat feedback itself. It created Hollowflux, an extremely fun and fast-paced hack ’n’ slash with beautiful simulated water and lighting effects.

I wanted to test Astra on a 2D game with fluids/water effects, and it did extremely well on the art style, fluid dynamics, and the combat feedback itself. It created Hollowflux, an extremely fun and fast-paced hack ’n’ slash with beautiful simulated water and lighting effects.

Thomas Ricouard

25,143 görüntüleme • 2 ay önce

The video for Thundercat and Mac Miller’s “She Knows Too Much” incorporates both 2D and 3D elements—as Mac and Thundercat navigate through interdimensional worlds. Super dope. Long live Mac.

The video for Thundercat and Mac Miller’s “She Knows Too Much” incorporates both 2D and 3D elements—as Mac and Thundercat navigate through interdimensional worlds. Super dope. Long live Mac.

Complex Music

57,768 görüntüleme • 8 ay önce

We're running a playtest for Fright Train's demo!! Shoot monsters and maintain a train rushing through Antarctica as special agent Doug Barker! We're eager to get your feedback and suggestions! :)

We're running a playtest for Fright Train's demo!! Shoot monsters and maintain a train rushing through Antarctica as special agent Doug Barker! We're eager to get your feedback and suggestions! :)

WildArts Games

14,784 görüntüleme • 7 ay önce

3D animation is as good as 2D if done well

3D animation is as good as 2D if done well

Animelover

812,964 görüntüleme • 1 yıl önce

RealityScan is now available for Android devices, as well as iOS! Create high-fidelity 3D models from pictures taken with your phone or tablet today. Find out more and download for free:

RealityScan is now available for Android devices, as well as iOS! Create high-fidelity 3D models from pictures taken with your phone or tablet today. Find out more and download for free:

RealityScan

190,882 görüntüleme • 3 yıl önce

The Australian 3D series "Shaun Tan's Tales from Outer Suburbia" (by Flying Bark studio) has been quietly available for free on BYUtv for months (in the U.S.), and it also includes some 2D segments. >> I made this short video as a friendly reminder.

The Australian 3D series "Shaun Tan's Tales from Outer Suburbia" (by Flying Bark studio) has been quietly available for free on BYUtv for months (in the U.S.), and it also includes some 2D segments. >> I made this short video as a friendly reminder.

Catsuka

32,513 görüntüleme • 3 ay önce

Starting with a 3D model? Bad idea right 🤔 ⁺˚*•̩̩͙✩•̩̩͙*˚⁺‧͙⁺˚*•̩̩͙✩•̩̩͙*˚⁺‧͙⁺˚*•̩̩͙✩•̩̩͙*˚⁺‧͙⁺˚*•̩̩͙✩•̩̩͙*˚⁺‧͙⁺˚*•̩̩͙✩•̩̩͙*˚⁺‧͙ I made this to reveal my model on TikTok and thought I'd post it here as well c: (link on my carrd) I have my reasons for choosing 3D over 2D but I'd like to save that story for my debut ^^

Starting with a 3D model? Bad idea right 🤔 ⁺˚•̩̩͙✩•̩̩͙˚⁺‧͙⁺˚•̩̩͙✩•̩̩͙˚⁺‧͙⁺˚•̩̩͙✩•̩̩͙˚⁺‧͙⁺˚•̩̩͙✩•̩̩͙˚⁺‧͙⁺˚•̩̩͙✩•̩̩͙˚⁺‧͙ I made this to reveal my model on TikTok and thought I'd post it here as well c: (link on my carrd) I have my reasons for choosing 3D over 2D but I'd like to save that story for my debut ^^

Bijou Vos 💎 Diamond Fox ⟡ comms soon!

141,393 görüntüleme • 3 yıl önce

Finally got to take GPT 6.1 Sol for a spin. Decided to mix 2D and 3D together for a cosy country escape experience. GPT 6.1 Sol handles consistency very well - and was able to generate all the 3D assets. Worked well with Spriterrific for 2D sprites and custom animations.

Finally got to take GPT 6.1 Sol for a spin. Decided to mix 2D and 3D together for a cosy country escape experience. GPT 6.1 Sol handles consistency very well - and was able to generate all the 3D assets. Worked well with Spriterrific for 2D sprites and custom animations.

Chong-U

18,736 görüntüleme • 1 ay önce

LLaVA-3D A Simple yet Effective Pathway to Empowering LMMs with 3D-awareness Recent advancements in Large Multimodal Models (LMMs) have greatly enhanced their proficiency in 2D visual understanding tasks, enabling them to effectively process and understand images and videos. However, the development of LMMs with 3D-awareness for 3D scene understanding has been hindered by the lack of large-scale 3D vision-language datasets and powerful 3D encoders. In this paper, we introduce a simple yet effective framework called LLaVA-3D. Leveraging the strong 2D understanding priors from LLaVA, our LLaVA-3D efficiently adapts LLaVA for 3D scene understanding without compromising 2D understanding capabilities. To achieve this, we employ a simple yet effective representation, 3D Patch, which connects 2D CLIP patch features with their corresponding positions in 3D space. By integrating the 3D Patches into 2D LMMs and employing joint 2D and 3D vision-language instruction tuning, we establish a unified architecture for both 2D image understanding and 3D scene understanding. Experimental results show that LLaVA-3D converges 3.5x faster than existing 3D LMMs when trained on 3D vision-language datasets. Moreover, LLaVA-3D not only achieves state-of-the-art performance across various 3D tasks but also maintains comparable 2D image understanding and vision-language conversation capabilities with LLaVA.

LLaVA-3D A Simple yet Effective Pathway to Empowering LMMs with 3D-awareness Recent advancements in Large Multimodal Models (LMMs) have greatly enhanced their proficiency in 2D visual understanding tasks, enabling them to effectively process and understand images and videos. However, the development of LMMs with 3D-awareness for 3D scene understanding has been hindered by the lack of large-scale 3D vision-language datasets and powerful 3D encoders. In this paper, we introduce a simple yet effective framework called LLaVA-3D. Leveraging the strong 2D understanding priors from LLaVA, our LLaVA-3D efficiently adapts LLaVA for 3D scene understanding without compromising 2D understanding capabilities. To achieve this, we employ a simple yet effective representation, 3D Patch, which connects 2D CLIP patch features with their corresponding positions in 3D space. By integrating the 3D Patches into 2D LMMs and employing joint 2D and 3D vision-language instruction tuning, we establish a unified architecture for both 2D image understanding and 3D scene understanding. Experimental results show that LLaVA-3D converges 3.5x faster than existing 3D LMMs when trained on 3D vision-language datasets. Moreover, LLaVA-3D not only achieves state-of-the-art performance across various 3D tasks but also maintains comparable 2D image understanding and vision-language conversation capabilities with LLaVA.

AK

41,747 görüntüleme • 2 yıl önce

Move the MetaHuman rig to custom mesh characters, turn 2D images into 3D models, and transfer skin data for free with Loading studio's art tools for Maya, free in January. Sign up: #maya #3dart #gamedev #gamedevelopment #digitalart

Move the MetaHuman rig to custom mesh characters, turn 2D images into 3D models, and transfer skin data for free with Loading studio's art tools for Maya, free in January. Sign up: #maya #3dart #gamedev #gamedevelopment #digitalart

80 LEVEL

99,059 görüntüleme • 2 yıl önce

Animation studio BONI IS SCARED talked to us about creating EUTHANAZIES, a dystopian thriller animated series, using Substance 3D Painter, Blender, and Marvelous Designer, and discussed the project idea, tricks for combining 2D and 3D, and custom Geometry Nodes setups for cables and snow. "The 2D elements were used for a lot more than just adding details on top of the renders. We used hand-drawn textures and normals to help merge the 2D and 3D, as well as smear frames and hand-drawn motion blur. We also wanted to break some of the physical rules of the 3D world. We worked with hand-painted shadows and distorted perspectives, sometimes deforming entire environments to get the composition we wanted." Read the full interview:

Animation studio BONI IS SCARED talked to us about creating EUTHANAZIES, a dystopian thriller animated series, using Substance 3D Painter, Blender, and Marvelous Designer, and discussed the project idea, tricks for combining 2D and 3D, and custom Geometry Nodes setups for cables and snow. "The 2D elements were used for a lot more than just adding details on top of the renders. We used hand-drawn textures and normals to help merge the 2D and 3D, as well as smear frames and hand-drawn motion blur. We also wanted to break some of the physical rules of the 3D world. We worked with hand-painted shadows and distorted perspectives, sometimes deforming entire environments to get the composition we wanted." Read the full interview:

80 LEVEL

56,131 görüntüleme • 28 gün önce

An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion discuss: We introduce a new approach for generating realistic 3D models with UV maps through a representation termed "Object Images." This approach encapsulates surface geometry, appearance, and patch structures within a 64x64 pixel image, effectively converting complex 3D shapes into a more manageable 2D format. By doing so, we address the challenges of both geometric and semantic irregularity inherent in polygonal meshes. This method allows us to use image generation models, such as Diffusion Transformers, directly for 3D shape generation. Evaluated on the ABO dataset, our generated shapes with patch structures achieve point cloud FID comparable to recent 3D generative models, while naturally supporting PBR material generation.

An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion discuss: We introduce a new approach for generating realistic 3D models with UV maps through a representation termed "Object Images." This approach encapsulates surface geometry, appearance, and patch structures within a 64x64 pixel image, effectively converting complex 3D shapes into a more manageable 2D format. By doing so, we address the challenges of both geometric and semantic irregularity inherent in polygonal meshes. This method allows us to use image generation models, such as Diffusion Transformers, directly for 3D shape generation. Evaluated on the ABO dataset, our generated shapes with patch structures achieve point cloud FID comparable to recent 3D generative models, while naturally supporting PBR material generation.

AK

66,852 görüntüleme • 2 yıl önce

We plan on recruiting some community members for research purposes to review the “CODE NAME: PROJECT INVENTORY” app in Q1 2024. These community members will participate in design working sessions and also provide feedback on different use cases. A HUGE shout-out to Jarlan Perez for leading the effort, as well as members of the RTFKT Engineering and 3D teams for their work on this.

We plan on recruiting some community members for research purposes to review the “CODE NAME: PROJECT INVENTORY” app in Q1 2024. These community members will participate in design working sessions and also provide feedback on different use cases. A HUGE shout-out to Jarlan Perez for leading the effort, as well as members of the RTFKT Engineering and 3D teams for their work on this.

RTFKT

95,290 görüntüleme • 2 yıl önce