Skip to main content

LUP Student Papers

LUND UNIVERSITY LIBRARIES

Detecting Nucleated Cells in Bone Marrow Smears using Deep Learning

Bram, Robin LU and Näsström, Mattias LU (2021) In Master’s Theses in Mathematical Sciences FMAM05 20211
Mathematics (Faculty of Engineering)
Abstract
Being able to detect nucleated cells in human blood is a very important part of health care. CellaVision has machines which can automatically detect cells in blood samples from peripheral blood instead of using manual microscopy. Sometimes it is not enough to only investigate the peripheral blood but also samples from the bone marrow. The bone marrow is different from the peripheral blood and it is generally more difficult to detect cells in. The aim of this master's thesis is to produce a machine learning model that can detect nucleated cells in bone marrow smears.

We investigated several different models to see which model would yield the best performance while being sufficiently fast. After having found the type of model that worked... (More)
Being able to detect nucleated cells in human blood is a very important part of health care. CellaVision has machines which can automatically detect cells in blood samples from peripheral blood instead of using manual microscopy. Sometimes it is not enough to only investigate the peripheral blood but also samples from the bone marrow. The bone marrow is different from the peripheral blood and it is generally more difficult to detect cells in. The aim of this master's thesis is to produce a machine learning model that can detect nucleated cells in bone marrow smears.

We investigated several different models to see which model would yield the best performance while being sufficiently fast. After having found the type of model that worked best, we investigated different improvement techniques such as hyperparameter optimization, active learning and pseudo labeling to see if this could help improve the network's performance. Our results show that we found a fast enough model that could detect nucleated cells in bone marrow smears with a good performance and that the performance improved after application of the improvement techniques. (Less)
Please use this url to cite or link to this publication:
author
Bram, Robin LU and Näsström, Mattias LU
supervisor
organization
course
FMAM05 20211
year
type
H2 - Master's Degree (Two Years)
subject
publication/series
Master’s Theses in Mathematical Sciences
report number
LUTFMA-3446-2021
ISSN
1404-6342
other publication id
2021:E27
language
English
id
9047351
date added to LUP
2021-06-08 17:01:11
date last changed
2021-06-08 17:01:11
@misc{9047351,
  abstract     = {{Being able to detect nucleated cells in human blood is a very important part of health care. CellaVision has machines which can automatically detect cells in blood samples from peripheral blood instead of using manual microscopy. Sometimes it is not enough to only investigate the peripheral blood but also samples from the bone marrow. The bone marrow is different from the peripheral blood and it is generally more difficult to detect cells in. The aim of this master's thesis is to produce a machine learning model that can detect nucleated cells in bone marrow smears.
 
We investigated several different models to see which model would yield the best performance while being sufficiently fast. After having found the type of model that worked best, we investigated different improvement techniques such as hyperparameter optimization, active learning and pseudo labeling to see if this could help improve the network's performance. Our results show that we found a fast enough model that could detect nucleated cells in bone marrow smears with a good performance and that the performance improved after application of the improvement techniques.}},
  author       = {{Bram, Robin and Näsström, Mattias}},
  issn         = {{1404-6342}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Master’s Theses in Mathematical Sciences}},
  title        = {{Detecting Nucleated Cells in Bone Marrow Smears using Deep Learning}},
  year         = {{2021}},
}