Not surprisingly, a number of these applications were ones that can be installed on the new iPhone 2.0 software. Some of these apps are cool enough to warrant their own posting. Others I'll mention below.
For anyone teaching anatomy to students, apps such as Netter's Anatomy Flash Cards are pretty obvious choices. Pulling up an organ or a muscle on my iPhone is sometimes a lot quicker than dumpster-diving for a similar web-based picture on our workstations.
The audience especially liked my description of Shazam, which has nothing at all to do with radiology.
It works like this:
- you hear an unfamiliar song on the radio
- you hit the "Tag Now" button
- the app listens for about 15 seconds, and then queries the Shazam server
- you then get back a reply that looks like this:
As you can see, a successful hit not only returns the name of the tune, album and band, but also cover art and a link to the iTunes store where you can get your own copy. When available, a YouTube video link also pops up. At the end of a session of listening, Shazam displays a list of all the songs you've just been listening to.
How does it work? The Shazam site says it is "powered by the world's leading music recognition technology". However, for all I know, this "technology" may actually be students chained in dungeons and fed beer and pizza through IV tubing.
However it works, my son and I had a rather large time using this app on our drive back and forth between the Denver airport and the meeting site in Vail. Shazam worked fine with most of the pop, rock and country stations we monitored. However, it had no luck at all with the few ethnic and classical stations we tried.
It's not much of a stretch to imagine a Shazam-like iPhone app for radiological diagnosis. Non-radiologists could someday point their iPhones at an image, and then upload image features somewhere into the cloud for interpretation. Fortunately for the bottom lines (and bottoms) of radiologists everywhere, medical image analysis seems to be a lot tougher problem than top-40 musical analysis.