Universe

102322_malig_norm Computer Vision Dataset

byJack LiTask:
Object Detection
License:CC BY 4.099 views8 downloads
See all 1.7k images102322_malig_norm cells sample showing 0, 1, 2, 3102322_malig_norm cells sample102322_malig_norm cells sample showing 1, 2102322_malig_norm cells sample102322_malig_norm cells sample102322_malig_norm cells sample102322_malig_norm cells sample102322_malig_norm cells sample showing 1, 3102322_malig_norm cells sample102322_malig_norm cells sample showing 0, 2102322_malig_norm cells sample showing 0102322_malig_norm cells sample showing 0, 3

About 102322_malig_norm Dataset

Here are a few use cases for this project:

Use Case 1: Early Cancer Detection and Diagnosis

  • The "102322_malig_norm" computer vision model can be used by medical professionals to analyze microscope images of cell samples, aiding in the early detection and diagnosis of cancer by accurately identifying and classifying cancerous cells.

Use Case 2: Tracking Treatment Progress

  • Oncologists can use this computer vision model to monitor the progress of patients undergoing cancer treatments. By comparing cell classifications in images taken before, during, and after treatment, medical professionals can determine the treatment's effectiveness and adjust the approach if needed.

Use Case 3: Analysis of Body Fluid Samples

  • The model can be used to process body fluid samples, such as blood, urine, or spinal fluid, to identify and classify the presence of abnormal cells. This can provide further evidence of cancerous growth or other diseases with cellular manifestations.

Use Case 4: Biomedical Research

  • Scientists can use this computer vision model to streamline their research on cellular phenomena, including cancer cell progression, metastasis, and drug resistance. The automated classification of cells from microscopy images enables quicker and more accurate data analysis, accelerating the advancement of knowledge in these areas.

Use Case 5: Education and Training

  • The "102322_malig_norm" computer vision model can assist in the education and training of medical students, biologists, and other researchers by providing an automated tool to practice cell classification and identification. Visualizing cell classes in this manner can help students develop a deeper understanding of cellular morphology and pathology.

Use Free 0, 1 and 2 Detection API

Powered by general detection model

Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "0, 1, 2, 3, Cancer"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ 102322_malig_norm_dataset,
  title = { 102322_malig_norm Dataset },
  type = { Open Source Dataset },
  author = { Jack Li },
  howpublished = { \url{ https://universe.roboflow.com/jack-li/102322_malig_norm } },
  url = { https://universe.roboflow.com/jack-li/102322_malig_norm },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

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