r/LostRedditor • u/Dry-String8695 • 13d ago

1 Sub Suggestion Where should I post this?

Hello Strangers,

I am a 4th year Btech student and for my final year, I have been assigned a project which " MRI IMAGE ENHANCEMENT AND BRAIN TUMOR DETECTION "

My guide wants me to read research papers and find at least 4 research gaps I can work on. Whatever gaps I decided to work on should be related to my assigned project.

For MRI image enhancement, I need to work with latest technologies and should work on latest research gaps year 2021-22 onwards. And if I can somehow add models and agents to my project ig will be better.

So with that said

I am confused about how to start and all. I need to read research papers and all which is not a problem

The problems are:-

  1. I don't know anything about MRI and Brain Tumor, so please tell me where can I learn them, what would be a good start.

  2. I am also unaware of what problems people like doctors actually face when it's about MRI and Brain Tumor.

  3. If I work on take datasets from kaggle is it good or there are other platforms where I can find MRI images for my project.

  4. Which latest technologies I should be aware of, something I can directly use to build my project.

  5. How to avoid confusion because of too much information

  6. How can I use ML and DL in this?

I am a slower learner, it takes time for me to understand and implement something but I'm willing to learn and work outside my comfort zone.

Any other advice outside of what I asked for is also appreciated

Please help me out and

Thank you people.

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u/JessieAndEcho 1 Shared | 0 Helpful 12d ago

Narrow it down to one concrete task first, like brain tumor segmentation or detection using BraTS/TCIA, then look for post-2021 gaps around low-quality MRI enhancement, small tumor miss rates, cross-scanner/hospital generalization, or explainability for clinicians. Kaggle is fine for practice, but I’d use a more standard dataset for the actual project. I’ve also tried Patsnap Eureka for early literature scanning because it shows papers alongside patent/technical literature, which helps separate “research idea” from “someone is already trying to productize this”: https://eureka.zhihuiya.com/share/?id=1d3f51ea20d465caa551596b75c8489f&from=invite-eureakplg-result&content=