Medical and Biomedical Image Processing - Science topic

I am trying to get an insight of the above mentioned research paper, specially about the filtering process used to remove grid artifacts. However, I find it difficult to understand it correctly.

I would be much grateful if anyone could help me to clarify a few questions that I have.

My questions are as follows:

1) what are the pixel values of the Mean filter they used? they mention about using an improved Mean filter, but what is the improvement?

2) do they apply the Mean filter in the whole patch image (seems like it), or only in the grid signal region (characteristic peak range)?

3) what do they mean by (u1,v1) being Fmax value? does that mean that the center pixel of the Mean filter is replaced by this max value?

Thanks in advance!

Image compression.

Suppose I have a dicom file with pixel size (0.5,0.5), and I want to make the pixel size to (0.7,0.7) or vice versa. How can I change/modify the pixel size of a dicom file?

Greetings!

I am new to x-ray radiology, and working on a project where I am supposed to compute the thickness of the subject being examined. I found a technical paper published by Fuji inc. ("Improvement in Image Quality and Workflow of X-Ray Examinations using a New Image Processing Method, Virtual Grid Technology"), where it is shown that the thickness can be calculated using the x-ray dose absorbance (figure 5 of the paper). My idea is to apply the Beer-Lambert law on 2D images that I capture before-and-after placing the subject; and to solve the natural logarithm at each corresponding pixel location to obtain a 2D thickness image. I would be very grateful if you could advise whether this is the correct way of computing the thickness. Thank you in advance!!

Dear researchers.

I have recently started my research in detecting and tracking brain tumors with the help of artificial intelligence, which includes image processing.

What part of this research is valuable, and what do you suggest for the most recent part that is still useful for a PhD. research proposal?

Thank you for participating in this discussion.

I'm working of DICOM images for the project I need multiple segmentation in one volume, anyone interested?

I have recorded hologram is best on digital in-line holography technique. The distance between the objects and the sensor (CMOS sensor,taking from web cam) is typically 5 mm. The illumination source is LED ,that is placed at a distance of 5 cm from the sample and is filtered through a large pinhole having a diameter of 0.1 mm .

Any short introductory document from image domain please.

Medical Imaging.

During preprocessing medical image data different techniques should be considered such as cropping, filtering, masking, augmentation. My query is, which techniques are frequently applied to medical image datasets during pre-processing?

I have searched about the REVIEW database but I can't find it for download. besides, The vampire dataset is not a public database. So, I had sent vampire non-commercial license to use the annotation tool. But they didn’t answer.

could anybody send me the datasets?

I'm looking for a PhD position and opportunity in one of the English speaking university in European countries (or Australia).

I majored in artificial intelligence. I am in the field of medical image segmentation and My thesis in master was about retinal blood vessels extraction based on active contour. Skilled in Image processing, machine learning, MATLAB and C++.

So could anybody helps me to find a prof and PhD position related on my skills in one of the English speaking university?

I am an engineer/researcher  developing code for finding feature parameters of irregular shaped 2d closed curves . For example a square has 4 corners and one width/height , circle infinite corners/radius, oval infinite corners/ 2 lengths major and minor. So I was wondering if we could have various measure for real life curves as found in US cardiac images such as width of the ventricles.Any help would be deeply appreciated.

Thanks,

Sushma

I would like to research on MR images (0.5T and 3T). Can you please suggest some websites that I can download dataset including both 0.5T and 3T MR images? Thank you.

I am trying to train a UNET architecture built with the PyTorch library. I am looking for the best methods to load my data into the model. the dataset has around 500 images (RGB image of around 3000x4000 pixels).

I am planning to extract patches of an image into (256,256,3) shaped patches alone with augmentation while training.

I am looking at methods that do not overload the ram at the same time not compress the data too much to lose the quality of data.

Images are required for testing and validation of a new technique.

For my research I need cancer( tumor) digital pathology image database.Type of cancer is not important but the data should have labels.

I would like to do research on MRI images. Can you please suggest some websites from where MRI images can be downloaded. Thanking you. Gautam Talukdar. 

I am working on Medical image segmentation Problems, I would like to know is there any public dataset available for Lung and Liver images

Before displaying an ultrasound image, the machine usually performs a logarithmic compression in order to better visualise an image in terms of grayscale. In order to treat a DICOM image, is it necessary to do a logarithmic decompression for more accurate results of image analysis and processing?

I am working with image processing techniques on breast thermograms.

I need a "public" benchmark image dataset for prostate segmentation. Images can be CT/MR/ultrasound (preferably MRI) but at least 3 experts, ideally more,  must have segmented each image.

I am a university student and I am doing research in medical image processing.

I need the adolescent (12 to 18 years old) brain T1 and diffusion-weighted images data set.

Actually , I really need this to conduct my research. Could anyone please help me to find a dataset for that?

Iris recognition.

I know that in List mode data the scintillating events are stored along with the time stamps of the event. I have a doubt regarding image reconstruction from the list mode data.

Is each (x,y coordinate of) photon count binned into an image matrix or are the photon counts integrated in certain time interval and treated with Anger algorithm or MLEM algorithm then binned into a image matrix? If the latter is the case then what is the value of the time interval?

If my question is not clear or wrong can anybody suggest some sources which will help me in understanding this ?

CTU-UHB Intrapartum CTG database consists of CTG records and clinical information. The data in database has been extracted from the OB TraceVue system to an open format using software. I need the raw data of this database. The database contains .dat and .hea file. But i cann't find a way to extract the raw data in the database. Can anyone help me?

we need a 4D untrasound device that allows personal laptops to be the main part of the scanner with endaroscope ,echo cardioscope ,vaginal ,rectal and abdominal  sonic probes as attachments, is there any available? how effective.

I have done by both UG and PG in Biomedical Engineering. I would like to peruse my PhD in Medical image processing/Analysis with machine learning for prediction. My area of focus would be either cancer images or Neuro images. After completing PhD other than teaching what is the scope?Please help.

I've recently started pursuing PhD in Medical Image Processing. I am struggling to find a suitable problem to carry out research.

I was initially interested in working on brain images but after doing studies and according to peers' advices lots of works have already done with brain, but still work can be done on:

1. Retinal images

2. Chest radiography

3. Estimating probability of lung cancer etc.

I would be obliged if somebody suggests me some relevant topics(related to brain or other organs) where still there are lots of scopes to work on.

I wonder if anyone has a recipe for a gel phantom for using for USS training.

for vascular grafts

For medical image processing research.

ISI rapid publication journals.

Hi,

I want to use a MRI images dataset in order to detect heart failure with image processing techniques. In the beginning I should choose the kind of map I need. T1 map or T2 map, I should choose one of them.

But I don’t know what is the differences between them and which one is better for detecting heart failure.

Can anyone share some information about that?

In what diameter size a lung nodule in CT scan is considered malignant nodule, for example in luna16 dataset there is annotation file called 'annotations.csv' that contains a nodule diameter, if I want to use this file for classification purpose based on diameter size, what is the range of diameter size that I can choose it as malignant nodule. kindly give me your answer based on a knowledge or a reference?

Hello everyone,

I am currently developing my method for 3D image segmentation of medical images (CT and MRI), so I would like to see if anyone have any published papers on this subject, along with the source code written in MATLAB so that I could compare my method against it?

I want to compare the segmentation accuracy and time efficiency and test my algorithm against existing methods, preferably that have been published recently in renowned journals with impact factor?

Thanks in advance!

In many dead cases there is useful information available in dead person's brain missing which can be used for discovering one's mind regarding different events happened to him or his relatives. I was wondering if there's any solution to extract information based on dead one's brain signals.

Could you please point me out to some successful Signal, image, or video processing real life applications using partial differential equation?

Preferably, involving heat, reaction-diffusion, Poisson, or Wave equation.

If possible in fuzzy environment.

Best regards

Sarmad.

Hello all,

I am a researcher working on color image processing and have knowledge in Machine Learning and Programming. Currently, I am planning to deviate my research towards the Medical and Biomedical application. Suggest some research topics in Medical/Biomedical application which has scope in future?

I have developed a method using which the edges in images are get enhanced. Which evaluation metric shall I use to state that edges in image are improved or not? I am working on brain tumor images.

hi all

The benefits of Multilevel Image Segmentation Versus 2-level Image Segmentation? 

thanks

I'm using the batch scripts generated by SPM12 in my own Matlab codes. I'm trying to use "deploytool" in Matlab2015b to compile my codes into an "exe" file. I've included SPM12 as the required files to run the program. But when I run the "exe" file, I got errors as follows:

> Undefined function or variable 'cfg_mlbatch_appcfg_master'.

> Error in cfg_util>local_initapps (line 1440)

> Error in cfg_util (line 743)

> Error in spm_jobman (line 189)

One link I found online related to this problem is not helpful: https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1606&L=spm&F=&S=&P=612689

I don't know if anyone knows how to solve this problem.

Thanks!

I am working on emotion recognition using a pretrained DCNN for feature extraction. I have obtained 1 X 1000 features from the DCNN. And i want to reduce its dimensionality. PCA have been suggested. But I want to know if there are better alternatives for PCA.

The files has the extention .vol, and the format is called "Kretzfile". It is a 4D ultrasonic study for fetal heart analysis. Doctors called the analysis STIC (Spatio-Temporal Image Correlation). The images were adquired using an ultrasound system "Voluson 730" of General Electric. I need the images for my research project related to segmentation and optical flow estimation.

I am interested to segment it (somehow) and get the motion information from an echo of the heart. Any comment also on this part?

I am using Dice score to compare image segmentation.

But what is the significance of Kappa score, Positive predictive Value and Jaccard coefficient with respect to Image segmentation?

How can use these values to tune my algorithm?

Hi. I am currently working on a medical image processing project that segments the coronary artery blobs from the axial CT slices of the human heart and converts the segmented coronary blob slices to a 3D coronary artery model. I wish to extend my project by mapping the 3D model to the 2D axial input slices, ie, by clicking on a point in the 3D model, it must display the appropriate CT slice and also the point to the position in that slice. Are there any methods ( techniques ) or softwares available to do this? If so, how?

I am using OpenCV to implement this project.

By physical dimensions, I mean that the spatial resolution of the images is specified in terms of millimetres. 

I'm trying to analyse images of animal tissues produced with a 3DHistech slide scanner. I usually use ImageJ but have problems fitting large enough images in the memory. Are there any other free alternatives, or tricks that could be used with ImageJ? My analysis is simple, just detecting & measuring circular holes of certain size (adipocytes). The images are like 25000 pixels x 25000 pixels.

Thanks in advance for your replies.

Does anybody know any software which can convert pictures from MHA format to .raw format?

I used visualization-MITK workbench2016.11.0 software, but it has not such convertor. 

I want to evaluate my 3D tumor segmentation and I do not have any idea how to evaluate that?

Regards

Ali

I would like to get sample tomosynthesis imaging

I have 83 ct dicom series image  and I want to remove patient table from these image.for this purpose I write the following code in the MATLAB software:

a = dicomread('E:\dicom\44.dcm');

b=double(a);

sample=a(50:100,250:300);

background=mean(mean(sample));

for i=1:512;

for j=1:512;

if i>385;

b(i,j)=background;

end

end

end

image=dicomwrite(b,uint16(b),'44.dcm');

after I run this code patient table  remove from my image but image contrast is unacceptable.

how to  adjust image contrast with matlab?

please help me.

Any help would be much appreciated. Thanks.

Any one 

Lung Imaging

Respected all,

I need Follicular Lymphomas tissue sample for my project. If anyone of you have information regarding that please share to me 

Thanks in advance

I would like to detect edges on 3D MRI images but with intensities variations in the some regions, I keep obtaining false edges.

I applied canny edge detection on the image prceeded with anisotropic filtering and you can see the false edges in the attached picture (green circles )

Is there some processing strategy that can solve this problem?

I know several quantitative quality measures for contrast enhancement in medical images, but sometimes is not enougth and I need the opinion of physicians about the visual quality of the processing.

Are there procedures, surveys, instruments, software to do that?

I need some public digital tomosynthesis datasets for detection of lung nodules.

Is there any method for the selection of best wavelet for the texture classification for medical images? 

I'm doing an imaging study in patients with sciatic nerve radiculopathy, and I'm trying to find out the vertebral level that is adjacent to where the L4, L5, and S1 nerve roots enter the cord.

I understand that there will likely be a large amount of variability among people, and most of the resources I've seen so far suggest that they enter the cord somewhere between the level of L1, T12, and T11 vertebrae.

Does anyone know of any studies (e.g. fiber tracing, DWI) that have attempted to more formally answer this question? 

Thanks for your help!

Dan

simple inflamed appendicitis has limitation in diagnosis using simple and cheap ultrasound machines. Any other way from new modern ultrasounds apart from clinical assessment and costly CT and MRI..

Hi, 

I have a set of segmented images and i want to select ,for each new image, the best match in this collection. witch algorithm can i use for such task?  

Thanks 

For e.g. if you have to represent head, right hand, left hand, waist , right leg and left leg what would be the most efficient way to do so? If anyone has used Labanotation, could you please tell me how the data is represented there? 

Which classification tool is better for Medical Image analysis. I am planning on working on medical images to facilitate image works within help sector.

I am finding difficult to read medical images (.dcm) in MATLAB. Please suggest.

I have several synthesized quantum dots and magnetic particles. I feel that they can be used as contrast agent for bio imaging. So for that I want to do some lab based experiment. Then go for animal model. So please guide me what are the primarily experiments that are possible to proceed in this area.    

I want to do research about retinal images and finally extract vessel and optic disk and exudates. but i cant find angiogram database.

who can help me?

and

you think which one is better for my Thesis? segmentation from fondus images(DRIVE) or angiography images?

A saliency map (2D image)and a segmented image(2D image) of same image is already having. On the basis of saliency map, i have to calculate average saliency for each region of segmented image.

We are trying to understand how capability of 3D tissue scaffolds made of polymers and ceramics is affected by their internal architectures. Currently, we have obtained a series of micro-CT images (about 300) of a polymer-made scaffold. We want to use imageJ to achieve 3D reconstruction and get to know overall porosity, surface area and distribution of pores and ratio between open and closed pores. 

I wonder if there are any imageJ plugins can do this. If not what other software can be used?

Your help will be very appreciated. 

Are there any metrics to compare the robustness of 2 features for an image? I need to compare and choose which feature vector would be apt for my spine image dataset.

i am trying to start research in medical image processing, which type of medical image is in recent research and which one is to better?

Hello Friends:

I'm sending out a general call for your help in deciding on a thesis topic for my MS degree. I had an MSEE and had worked as an electronics engineer for 20 years (in US Defense, FiberOptics, Data Storage, Machine Vision industries). Now decided to leave it behind and returned to school this past January 2016 for an MSBE degree (Ph.D. later on, God willing) since I wanted to meld my knowledge in electronics with the new field of bioengineering(new to me anyways). The problem is I have no life sciences background (Biology, Chemistry, BioChem, etc.) to speak of since high school (and that was a really long time ago!). All thesis project ideas I have seen are so biology/life science-based which I, unfortunately, can't do (without spending another year or two acquiring that knowledge). Designing standard bioelectronics devices such as heart rate monitors/pacemakers etc. bores me silly and honestly don't think one can submit that as a thesis topic as still be an honest individual. I have the following interests:

- Image Processing ... I designed an IP board as my MSEE thesis back in the day). Analyzing MRI scan images seem to have been done to death. Is it still a topic worthy of an MS degree? If so, any new challenges here?

- Bioimpedance measurements ... I'm new to this but find the whole concept intriguing and fascinating. But designing body fat measurement devices is also too boring and technically dumb. Not worth an MS degree in my opinion. Sorry!

- Biosensors ... new to them as a concept and find them also very intriguing and fascinating. But I'm afraid my lack of biology/biochemistry would be a hindrance and burden to me.

Any suggested project must be realistically doable within a 4-5 month timeframe, tops. I'd start in Spring 2017 then finish in the following summer.

Thanks All :)

- David

My requirement is to find the volume of the sample within the MRI image which consists of the sample, water and air. I have the data in the form of intensities in a 3D array of size 128*128*128 in which the sample corresponds to black pixels and the water volume corresponds to lighter pixels. Also, the outside air volume and the air bubbles present which are black. I am trying to use watershed function to find the connected sequence of pixels and finding the one with maximum frequency (I assume the sample to be the largest connected sequence of dark pixels), but somehow it is not detecting the sample volume as connected one. Also, bwconncomp and the labelmatrix are not of much help. Any suggestions/ideas on how to find this ?

Has anyone previously used K-nearest neighbour search method to verify co-registration of MRI Images? Greatly appreciate any insight into how this method can be applied for exactly that purpose.

For my research, I am doing MRI image analysis. I have the data in the form of gray levels (only 1 and 0 for dark and bright pixels) in a 3D array. I am looking for a solution to find the boundary between dark and white area and mark the boundary with gray(Similar to the red boundary of the black box as shown in the image). Is there a way to identify the whole boundary?

I have tried using bwboundaries() and bwtraceboundary() functions, but of not much use.

Thanks in advance