MD syntax fix to remaining image refs

Author: vinfnet

articles/confidential-computing/use-cases-scenarios.md

@@ -13,7 +13,7 @@ ms.custom: ignite-fall-2021
 # Use cases and scenarios
 Confidential computing applies to various use cases for protecting data in regulated industries such as government, financial services, and healthcare institutes. For example, preventing access to sensitive data helps protect the digital identity of citizens from all parties involved, including the cloud provider that stores it. The same sensitive data may contain biometric data that is used for finding and removing known images of child exploitation, preventing human trafficking, and aiding digital forensics investigations.
 
-:::image type="content" source="media/use-cases-scenarios/use-cases.png" alt-text="Screenshot of use cases for Azure confidential computing, including government, financial services, and health care scenarios.":::
+![Screenshot of use cases for Azure confidential computing, including government, financial services, and health care scenarios.](media/use-cases-scenarios/use-cases.png)
 
 This article provides an overview of several common scenarios for Azure confidential computing. The recommendations in this article serve as a starting point as you develop your application using confidential computing services and frameworks.
 
@@ -40,7 +40,7 @@ In this secure multi-party computation example, multiple banks share data with e
 
 Through confidential computing, these financial institutions can increase fraud detection rates, address money laundering scenarios, reduce false positives, and continue learning from larger data sets.
 
-:::image type="content" source="media/use-cases-scenarios/mpc-banks.png" alt-text="Graphic of multiparty data sharing for banks, showing the data movement that confidential computing enables.":::
+![Graphic of multiparty data sharing for banks, showing the data movement that confidential computing enables.](media/use-cases-scenarios/mpc-banks.png)
 
 ### Drug development in healthcare
 
@@ -62,7 +62,8 @@ Confidential compute is used here by placing the analysis application (in this e
 
 The aggregate data-sets from many types of sensor and data feed are managed in an Azure SQL Always Encrypted with Enclaves database, this protects in-use queries by encrypting them in-memory. This prevents a server administrator from being able to access the aggregate data set while it is being queried and analyzed.
 
-:::image type="content" source="media/use-cases-scenarios/iot-sensors.jpg" alt-text="Diverse sensors feeding an analysis solution inside a trusted execution environment. Operators have no access to in-use data inside the TEE.":::
+[![Diverse sensors feeding an analysis solution inside a trusted execution environment. Operators have no access to in-use data inside the TEE.](media/use-cases-scenarios/iot-sensors.jpg)](media/use-cases-scenarios/iot-sensors.jpg#lightbox)
+
 
 ## Legal or jurisdictional requirements