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The Nucleus01:32

The Nucleus

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The nucleus is a membrane-bound organelle that acts as a control center in a eukaryotic cell. It contains chromosomal DNA, which controls gene expression and precisely regulates the production of proteins within the cell. In contrast, the DNA inside the mitochondria and chloroplast only carries out functions that are specific to those organelles.
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The regulation of gene expression inside the nucleus is dependent on many factors, including the DNA structure. The...
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The Nucleus01:25

The Nucleus

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The nucleus is a membrane-bound organelle that acts as a control center in a eukaryotic cell. It contains chromosomal DNA, which controls gene expression and precisely regulates the production of proteins within the cell. In contrast, the DNA inside the mitochondria and chloroplast only carries out functions that are specific to those organelles.
Arrangement of DNA within Nucleus
The regulation of gene expression inside the nucleus is dependent on many factors, including the DNA structure. The...
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Adaptability of Cytoskeletal Filaments01:12

Adaptability of Cytoskeletal Filaments

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The cytoskeleton is a complex dynamic structure performing varied functions based on cellular requirements. The adaptability of the individual filaments in the cytoskeleton determines their ability to perform various functions within the cell. It can undergo rapid reorganization during processes like cell division or remain stable for several hours as in the interphase. The adaptability of these filaments depends on stringent regulatory mechanisms. The microfilament and microtubules of the...
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Natural Selection and Adaptation01:15

Natural Selection and Adaptation

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Natural selection, a fundamental concept in evolutionary biology, is the mechanism by which evolution is driven, favoring organisms that are best adapted to their environments. This process enhances their chances of survival and reproduction. Adaptation, a key outcome of this process, involves genetic modifications that optimize an organism's functionality under specific environmental challenges, such as extreme cold or thinner air at high altitudes.
Beyond physical adaptations,...
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Modified Boxplots00:57

Modified Boxplots

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A standard box and whisker plot informs us about the spread of the data in a given sample. One can identify the minimum value, maximum value, first quartile value, second quartile or median value, and third quartile.
However, the box plot does not tell the reader about outliers - values that lie far from the center of the data. We can modify the standard box and whisker plot to identify the outliers and visualize the actual spread of the data in a sample.
Initially, we calculate the adjusted...
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Introduction to Innate and Adaptive Immunity01:21

Introduction to Innate and Adaptive Immunity

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The human immune system is a complex defense mechanism that protects the body from harmful pathogens and foreign substances. It comprises two crucial components: innate and adaptive immunity.
Innate immunity is the body's natural, nonspecific defense system that acts quickly to protect against pathogens. It incorporates physical barriers like skin and mucous membranes and cellular elements such as phagocytes and natural killer cells. This part of our immune system provides an immediate,...
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Related Experiment Video

Updated: Jan 29, 2026

A Lightweight, Headphones-based System for Manipulating Auditory Feedback in Songbirds
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A Lightweight, Headphones-based System for Manipulating Auditory Feedback in Songbirds

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A Lightweight Modified Adaptive UNet for Nucleus Segmentation.

Md Rahat Kader Khan1, Tamador Mohaidat1, Kasem Khalil1,2

  • 1Electrical and Computer Engineering Department, University of Mississippi, Oxford, MS 38677, USA.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces mA-UNet, a novel deep learning model for accurate cell nucleus segmentation in microscopy images. It excels at identifying small nuclei and overcomes data imbalance, achieving superior performance on complex biological datasets.

Keywords:
UNetdeep learningimage segmentationnucleus segmentation

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Area of Science:

  • * Computational biology
  • * Biomedical image analysis
  • * Deep learning for microscopy

Background:

  • * Cell nucleus segmentation is vital for quantitative analysis in biological and biomedical research.
  • * Traditional methods and existing U-Net models struggle with small foreground objects and imbalanced datasets.
  • * Large model sizes in current methods lead to overfitting issues.

Purpose of the Study:

  • * To develop a novel deep learning architecture, mA-UNet, for improved cell nucleus segmentation.
  • * To address challenges in predicting small foreground elements and dataset imbalance.
  • * To evaluate the performance of mA-UNet against state-of-the-art models.

Main Methods:

  • * Introduction of the mA-UNet architecture, optimized for small foreground element prediction.
  • * Implementation of a data preprocessing strategy adapted from road segmentation to handle imbalanced datasets.
  • * Quantitative and qualitative evaluation on the 2018 Data Science Bowl dataset.

Main Results:

  • * mA-UNet achieved a Mean Intersection over Union (MIoU) score of 95.50%, outperforming UNet++.
  • * The proposed methodology demonstrated superior performance compared to other state-of-the-art models.
  • * mA-UNet was successfully implemented on Zynq UltraScale+ FPGA using VHDL, showing efficiency and scalability.

Conclusions:

  • * mA-UNet offers a significant advancement in cell nucleus segmentation for microscopy images.
  • * The model effectively handles small objects and imbalanced data, crucial for biological applications.
  • * The FPGA implementation highlights the model's efficiency and potential for real-time applications.